Motor and control method and device thereof, storage medium and computer program product

Abstract

The invention discloses a control method and device of a motor, the motor, a storage medium and a computer program product, and a closed-loop control system of the motor is provided with a current loop and a speed loop. The control method of the motor comprises the steps of designing a preset time control model for closed-loop control of the motor for compensating time-varying interference in the closed-loop control of the motor; in the closed-loop control of the motor, operation parameters of the motor are obtained; and according to the operation parameters of the motor, the current loop and the speed loop are controlled by using the preset time control model, so that closed-loop control of the motor is realized. According to the scheme, unknown time-varying interference in closed-loop control of the motor and time-varying interference introduced in a network transmission process are compensated by using a self-adaptive preset time control algorithm, so that the control precision of the motor is improved.

Description

Technical Field

[0001] The present invention belongs to the field of motor technology, and specifically relates to a motor control method, device, motor, storage medium and computer program product, and more particularly to a networked brushless DC motor vector control method, device, motor, storage medium and computer program product based on adaptive predetermined time control. Background Art

[0002] With the development of electronic power and microelectronics, brushless DC motors (BLDCs) have become widely used in household appliances, industrial control, aerospace, and other fields due to their low noise, high efficiency, and reliable performance. To achieve smoother operation and higher dynamic response, vector control methods for BLDC motors have been greatly developed. To control the speed or position of BLDC motors, related solutions use the PID (proportional-integral-differential) algorithm for closed-loop control of BLDC motors. However, interference is inevitable during the motor's startup and operation, affecting the motor's control accuracy.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The object of the present invention is to provide a motor control method, device, motor, storage medium and computer program product to solve the problem that in the speed control of a motor (such as a brushless DC motor), a PID algorithm is used in related schemes to perform closed-loop control of the motor, but there are inevitable interferences during the motor startup and operation processes, which affect the control accuracy of the motor. By utilizing an adaptive predetermined time control algorithm, the unknown time-varying interference in the closed-loop control of the motor and the time-varying interference introduced during the network transmission process are compensated, thereby improving the control accuracy of the motor.

[0005] The present invention provides a method for controlling a motor, wherein the closed-loop control system of the motor has a current loop and a speed loop; the method for controlling the motor comprises: designing a predetermined time control model for the closed-loop control of the motor, for compensating for time-varying interference in the closed-loop control of the motor; obtaining operating parameters of the motor during the closed-loop control of the motor; and achieving closed-loop control of the motor by controlling the current loop and the speed loop using the predetermined time control model according to the operating parameters of the motor.

[0006] In some embodiments, a predetermined time control model is designed for the closed-loop control of the motor to compensate for the time-varying interference in the closed-loop control of the motor, including: constructing a control system model of the motor; introducing the controlled quantity of the motor into the control system model of the motor based on the operating parameters of the motor; and introducing the adaptive estimation parameters of the motor based on the time-varying interference of the motor; performing coordinate transformation based on the introduced controlled quantity of the motor and the adaptive estimation parameters of the motor, and then using the command filtering backstepping method to design a controller to obtain the controller of the motor control system model; and solving the adaptive law of the motor control system model; using the controller of the motor control system model and the adaptive law of the motor control system model as the predetermined time control model to compensate for the time-varying interference in the closed-loop control of the motor.

[0007] In some embodiments, in the predetermined time control model, the controller and adaptive law of the motor control system model are expressed as follows:

[0008]

[0009] Where u is the controller, is an adaptive law, and The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of step n-1, m n is the difference between the command filter error and its compensation parameter, ρn represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

[0010] In some embodiments, according to the operating parameters of the motor, the predetermined time control model is used to control the current loop and the speed loop to achieve closed-loop control of the motor, including: in the closed-loop control of the motor, the predetermined time control model is introduced into both the current loop and the speed loop; according to the operating parameters of the motor, the closed-loop control of the motor is achieved by controlling the current loop and the speed loop.

[0011] In some embodiments, the current loop has a d-axis current part and a q-axis current part; the predetermined time control model is introduced into both the current loop and the speed loop, including: introducing the predetermined time control model into the speed loop to obtain a first PPT module; introducing the predetermined time control model into the d-axis current part of the current loop to obtain a second PPT module; and introducing the predetermined time control model into the q-axis current part of the current loop to obtain a third PPT module.

[0012] In some embodiments, the operating parameters of the motor include: the d-axis current id of the motor, the q-axis current iq of the motor, the angle θ of the motor, and the angular velocity ω of the motor; when the speed loop has a first PPT module and the current loop has a second PPT module and a third PPT module, closed-loop control of the motor is achieved by controlling the current loop and the speed loop according to the operating parameters of the motor, including: in the speed loop, the angular velocity ω of the motor and the preset target angular velocity ω* of the motor are passed through the first PPT module to output the q-axis target current iq* of the motor. ; In the d-axis current part of the current loop, the d-axis current id of the motor and the pre-set d-axis target current id* of the motor are passed through the second PPT module to output the d-axis reference voltage Ud* of the motor; in the q-axis current part of the current loop, the q-axis current iq of the motor and the q-axis target current iq* of the motor are passed through the third PPT module to obtain the q-axis reference voltage Uq* of the motor; according to the angle θ of the motor, the d-axis reference voltage Ud* of the motor and the q-axis reference voltage Uq* of the motor, the control signal of the inverter side of the motor is determined to realize closed-loop control of the motor.

[0013] Matching the above method, the present invention provides, on the other hand, a control device for a motor, wherein the closed-loop control system of the motor has a current loop and a speed loop; the control device for the motor comprises: a control unit, configured to design a predetermined time control model for the closed-loop control of the motor, for compensating for time-varying interference in the closed-loop control of the motor; an acquisition unit, configured to acquire the operating parameters of the motor in the closed-loop control of the motor; the control unit is further configured to realize closed-loop control of the motor by controlling the current loop and the speed loop using the predetermined time control model according to the operating parameters of the motor.

[0014] In some embodiments, the control unit designs a predetermined time control model for the closed-loop control of the motor to compensate for time-varying interference in the closed-loop control of the motor, including: constructing a control system model of the motor; introducing the controlled quantity of the motor into the control system model of the motor based on the operating parameters of the motor; and introducing the adaptive estimation parameters of the motor based on the time-varying interference of the motor; performing coordinate transformation based on the introduced controlled quantity of the motor and the adaptive estimation parameters of the motor, and then using the command filtering backstepping method to design a controller to obtain a controller of the motor control system model; and solving the adaptive law of the motor control system model; using the controller of the motor control system model and the adaptive law of the motor control system model as the predetermined time control model to compensate for time-varying interference in the closed-loop control of the motor.

[0015] In some embodiments, in the predetermined time control model, the controller and adaptive law of the motor control system model are expressed as follows:

[0016]

[0017] Where u is the controller, is an adaptive law, and The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of step n-1, m n is the difference between the command filter error and its compensation parameter, ρ n represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

[0018] In some embodiments, the control unit, based on the operating parameters of the motor and utilizing the predetermined time control model, realizes closed-loop control of the motor by controlling the current loop and the speed loop, including: in the closed-loop control of the motor, introducing the predetermined time control model into both the current loop and the speed loop; and realizing closed-loop control of the motor by controlling the current loop and the speed loop based on the operating parameters of the motor.

[0019] In some embodiments, the current loop has a d-axis current part and a q-axis current part; the control unit introduces the predetermined time control model in both the current loop and the speed loop, including: introducing the predetermined time control model in the speed loop to obtain a first PPT module; introducing the predetermined time control model in the d-axis current part of the current loop to obtain a second PPT module; and introducing the predetermined time control model in the q-axis current part of the current loop to obtain a third PPT module.

[0020] In some embodiments, the operating parameters of the motor include: the d-axis current id of the motor, the q-axis current iq of the motor, the angle θ of the motor, and the angular velocity ω of the motor; the control unit, when the speed loop has a first PPT module and the current loop has a second PPT module and a third PPT module, implements closed-loop control of the motor by controlling the current loop and the speed loop according to the operating parameters of the motor, including: in the speed loop, after the angular velocity ω of the motor and the preset target angular velocity ω* of the motor are passed through the first PPT module, outputting the q-axis target current of the motor iq*; in the d-axis current part of the current loop, the d-axis current id of the motor and the pre-set d-axis target current id* of the motor are passed through the second PPT module to output the d-axis reference voltage Ud* of the motor; in the q-axis current part of the current loop, the q-axis current iq of the motor and the q-axis target current iq* of the motor are passed through the third PPT module to obtain the q-axis reference voltage Uq* of the motor; according to the angle θ of the motor, the d-axis reference voltage Ud* of the motor and the q-axis reference voltage Uq* of the motor, the control signal of the inverter side of the motor is determined to realize closed-loop control of the motor.

[0021] Matching the above device, the present invention further provides a motor, including: the control device of the motor described above.

[0022] In accordance with the above method, the present invention further provides a storage medium, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the steps of the motor control method described above.

[0023] In accordance with the above method, the present invention further provides a computer program product, comprising a computer program, which implements the steps of the above motor control method when executed by a processor.

[0024] Therefore, the solution of the present invention is to obtain a controller and an adaptive law based on an adaptive predetermined time control algorithm (i.e., a PPT control algorithm), which are introduced into the current loop closed-loop and speed loop closed-loop control of the brushless DC motor to compensate for the unknown time-varying interference in the closed-loop control of the motor and the time-varying interference introduced during the network transmission process; thereby, by utilizing the adaptive predetermined time control algorithm, the unknown time-varying interference in the closed-loop control of the motor and the time-varying interference introduced during the network transmission process are compensated, thereby improving the control accuracy of the motor.

[0025] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present invention.

[0026] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 1 is a flow chart of an embodiment of a method for controlling a motor according to the present invention;

[0028] Figure 2 A flow chart of an embodiment of designing a predetermined time control model for closed-loop control of the motor in the method of the present invention;

[0029] Figure 3 1. A flow chart of an embodiment of the method of the present invention that utilizes the predetermined time control model to control the current loop and the speed loop;

[0030] Figure 4 1 is a flow chart of an embodiment of the method of the present invention for achieving closed-loop control of the motor by controlling the current loop and the speed loop;

[0031] Figure 5 Schematic diagram of the structure of an embodiment of a motor control device of the present invention;

[0032] Figure 6 It is a structural diagram of an embodiment of a networked control system with adaptive scheduled time;

[0033] Figure 7 A schematic structural diagram of an embodiment of a networked brushless DC motor vector control system based on adaptive scheduled time control;

[0034] Figure 8 Schematic diagram of the design flow of the controller corresponding to the scheduled time control PPT algorithm.

[0035] In conjunction with the accompanying drawings, the reference numerals in the embodiments of the present invention are as follows:

[0036] 102 - acquisition unit; 104 - control unit. DETAILED DESCRIPTION

[0037] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Considering that in the speed control of motors (such as brushless DC motors), related solutions use PID algorithms to perform closed-loop control of the motors, there are inevitable interferences during the motor startup and operation process, which affect the control accuracy of the motor. Specifically, however, the PID algorithms used in related solutions cannot compensate for the inevitable time-varying parameters and environmental interferences during motor operation, such as fluctuations in device performance caused by changes in ambient temperature, and current fluctuations caused by changes in the magnetic field during motor operation.

[0039] Due to the constraints of the above problems, the control accuracy of the motor is subject to certain constraints. In order to improve the above problems, the solution of the present invention proposes a motor control method, specifically a networked brushless DC motor vector control method based on adaptive predetermined time control, which uses an adaptive algorithm (i.e., a predetermined time control PPT algorithm) to compensate for unknown time-varying interference in the closed-loop control of the motor; at the same time, networked transmission is taken into account, and the time-varying parameters introduced in the networked transmission process are compensated, which has higher anti-interference performance and is conducive to improving the control accuracy of the motor. Among them, the practical prescribed time (PPT) control algorithm is a customized algorithm in the solution of the present invention.

[0040] In other words, the solution of the present invention employs an adaptive law to compensate for relevant interference and time-varying parameters, thereby improving the motor's anti-interference capability. Secondly, to achieve faster dynamic response, a PPT algorithm with time-determined control is incorporated into vector control to achieve higher control effectiveness. Finally, the impact of networked transmission on control performance is considered, which helps improve motor control accuracy.

[0041] According to an embodiment of the present invention, a method for controlling a motor is provided. Figure 1 The closed-loop control system of the motor has a current loop and a speed loop; in the solution of the present invention, as shown in FIG. Figure 1 As shown, the motor control method includes: steps S110 to S130.

[0042] In step S110, a predetermined time control model is designed in advance for the closed-loop control of the motor to compensate for the time-varying interference in the closed-loop control of the motor; specifically, the predetermined time control model is designed according to the adaptive predetermined time control algorithm, such as the controller u and the control law corresponding to the predetermined time control PPT algorithm.

[0043] At step S120 , in the closed-loop control of the motor, the operating parameters of the motor are obtained, specifically, the d-axis current id of the motor, the q-axis current iq of the motor, the angle θ of the motor, and the angular velocity ω of the motor.

[0044] In step S130 , closed-loop control of the motor is achieved by controlling the current loop and the speed loop using the predetermined time control model according to the operating parameters of the motor.

[0045] The solution of the present invention is to design an adaptive scheduled time control algorithm (i.e., scheduled time control PPT algorithm) to compensate for the time-varying interference encountered by the brushless DC motor during operation, thereby improving the accuracy of motor control. The closed-loop control of the brushless DC motor detects the information of the Q-axis phase-cut current (i.e., q-axis current) and the D-axis radial current (i.e., d-axis current) when the motor is running, and cooperates with the mechanical angle obtained by the position sensor to achieve precise position control. The algorithm is designed to compensate for the interference introduced by current acquisition and position information acquisition, thereby achieving higher accuracy and anti-interference of motor control. In addition, in order to better adapt to networked application scenarios, the time-varying parameter problem introduced by networked transmission has also been considered and compensated.

[0046] In some embodiments, a predetermined time control model is designed for the closed-loop control of the motor in step S110 to compensate for the time-varying interference in the closed-loop control of the motor. For details, see the following exemplary description.

[0047] The following combination Figure 2 The flowchart of an embodiment of the method of the present invention for designing a predetermined time control model for closed-loop control of the motor further illustrates the specific process of designing a predetermined time control model for closed-loop control of the motor in step S110, including: steps S210 to S240.

[0048] Step S210 : constructing a control system model of the motor, specifically constructing a brushless DC motor control system model according to an application scenario of the brushless DC motor.

[0049] In step S220, the controlled variable of the motor is introduced into the control system model of the motor based on the operating parameters of the motor; and the adaptive estimated parameters of the motor are introduced based on the time-varying interference of the motor. The time-varying constraints of the motor are introduced to achieve the purpose of enabling the preset control accuracy and response speed as described in the solution of the present invention.

[0050] In step S230 , after coordinate transformation based on the introduced controlled variable of the motor and the adaptive estimated parameters of the motor, a controller is designed using a command filter backstepping method to obtain a controller of the motor control system model; and an adaptive law of the motor control system model is obtained by solving the method.

[0051] Step S240 : Using the controller of the motor control system model and the adaptive law of the motor control system model as the predetermined time control model to compensate for time-varying disturbances in the closed-loop control of the motor.

[0052] In the solution of the present invention, first, an adaptive law is designed to compensate for related interference and time-varying parameters, thereby improving the anti-interference ability of the motor; second, in order to obtain a faster dynamic response effect, a predetermined time control PPT algorithm is designed in the vector control to achieve a higher control effect; finally, the impact of networked transmission on control performance is also considered, and the time-varying parameters introduced in the networked transmission process are compensated.

[0053] In some embodiments, in step S240, in the predetermined time control model, the controller and the adaptive law of the motor control system model are expressed as follows:

[0054]

[0055] Where u is the controller, is an adaptive law, and The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of step n-1, m n is the difference between the command filter error and its compensation parameter, ρn represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

[0056] Figure 8This is a schematic diagram of the design process of the controller corresponding to the scheduled time control PPT algorithm. In the solution of the present invention, in order to compensate for the interference in the environment and the system itself in the above process, a control method with higher anti-interference and control accuracy is designed, that is, a scheduled time control PPT algorithm is designed. Figure 8 As shown in the example. Figure 8 As shown in FIG, the design process of the controller corresponding to the predetermined time control PPT algorithm includes the following steps:

[0057] Step 1: Model Construction: First, a brushless DC motor control system model is constructed based on the application scenario of the brushless DC motor. The system model used below is universally applicable to systems of any order. In the solution of the present invention, in order to enable the algorithm to be applied to any order, the system order is expanded to n dimensions, where n is a positive integer greater than or equal to 2. The system order is determined by the physical properties of the control system itself and is realized by representing the controlled system model as a mathematical model. In this case, it refers to the mathematical model determined by the physical properties of the control system in which the brushless DC motor is located.

[0058] Considering the network transmission (i.e. Figure 6 The above brushless DC motor system can be summarized as follows:

[0059]

[0060] y=χ1 (1).

[0061] Where, and Represents the system status, Indicates control output. D i (t), and They represent unknown time-varying bounded parameters, unknown bounded external disturbances, known virtual control factors and known smooth functions (these functions are related to specific control systems). represents the derivative of the system state (the subscript refers to the state, and the value range of i has been given above), represents the nth system state (where n represents the system dimension / order), j i ( χ i ) represents the composite function of the first i system states, j n (χ) represents the composite function of all system states, χ i+1 represents the i+1th system variable, θ i and They represent the unknown bounded time-varying parameters and the known smooth function, D n(t) represents the unknown bounded external disturbance, χ1 represents the controlled signal and is also the first state variable of the system. q(u) is the quantized input of the system. is the controller to be designed. q(u) is the deformation of u during network transmission of the system. The final result of the solution of the present invention is q(u).

[0062] Step 2: Acquisition and introduction of controlled quantity.

[0063] z1(t)=y(t)-y r (t) represents the tracking error between the actual measurement value and the control expected value.

[0064] The controlled quantity acquisition here refers to the information obtained by sensors in motor control (such as Figure 7 The current information in the current sensor and the position information of the motor rotor obtained by the speed sensor) are then introduced into the calculation z1(t)=y(t)-y r (t), in our actual use, the formula will represent the difference between the desired motor current and the detected current, and also represent the difference between the desired motor stator angle and the actual detected angle, thereby introducing the controlled quantity into the calculation.

[0065] Step 3: Introduce time-varying constraints. To achieve the higher dynamic response speed mentioned in the solution of the present invention and allow for the preset control performance without relying on the initial state of the motor, it is necessary to introduce time-varying constraints. The specific steps for introducing time-varying constraints are: Introduce a time-varying constraint boundary Γ(t) to constrain the tracking error z1(t) between the actual measurement value and the control expectation value:

[0066]

[0067] Where, 0<T<∞ and They represent the controllable response time and steady-state control accuracy of the predefined system in steady state.

[0068] Formula (2) is the constraint boundary piecewise function introduced in the algorithm design. The first section of the function is used before reaching the artificially set steady-state time T, and the second section is used after reaching the artificially set steady-state time T. Among them, the response time T and the control accuracy They are all set artificially, t represents the running time of time, p represents a constant related to the system dimension / order, and the value range satisfies p satisfies 2p>n+1, n is the dimension or order of the controlled system. Formula (2) uses a piecewise function: It is related to the algorithm advantages proposed by the system for the solution of the present invention. T represents the system stabilization time expected by the designer. The goal of using a piecewise function is to use the expected accuracy after T is reached. Constrain the overall error.

[0069] Step 4: Coordinate system transformation. Coordinate system transformation is a condition created to solve the final control law. The specific steps of coordinate system transformation are: relax - The delay constraint bound of Γ(t)<z1<Γ(t) at the initial time makes the constraint infinite at the initial time, constructs the composite function and maps it to the interval (0,1]:

[0070]

[0071] Where c is the design parameter and λ(t) can be expressed as:

[0072]

[0073] The tracking error is finally converted to:

[0074]

[0075] Where h(λ(t)) represents the designed scaling function, λ(t) represents the function of the constraint bounds and the control error, c is the constant parameter to be adjusted by the designer, and b is a constant greater than 0 given by the designer. z1 and z1(t) both represent the tracking error between the actual measurement value and the control desired value.

[0076] Step 5: Solve the control law of the universal system model. The following is the calculation method and results:

[0077] Use command filter backstepping method to design controller and introduce coordinate transformation in, is α i The corresponding first-order command filter output, α i represents the virtual controller of step i, η i represents the error between the ith system state and the ith step virtual controller, χ i represents the i-th system state.

[0078] Among them, Y i is a design parameter, represents the command filter output of the i-th virtual controller, α i-1 represents the virtual controller at step i-1, represents the initial state of the filter output of the virtual controller command in step i, α i-1 (0) indicates the initial state of the virtual controller at step i-1. (Intermediate process)

[0079] In computer science and programming, command filtering generally refers to the process of filtering or transforming a sequence of commands or data streams to remove unwanted parts or modify the data format. Backtracking is often used in problem solving, especially in search and decision-making processes, when it is necessary to retrace previous steps to find a solution.

[0080] Through compensation and calculation, the final controller and adaptive law can be calculated:

[0081]

[0082] Where u is the controller, For the adaptive law, yes The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of the n-1th step and the command filter error compensation parameters of the nth step, m n is the difference between the command filter error and its compensation parameter, ρ n represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

[0083] The coordinate transformation here is to simplify the calculation of the design process and avoid the generation of a large number of complex intermediate variables during the design process. It serves the final design goal of step 4. The final tracking error conversion in step 4 is the control purpose, which is to enable the control target to achieve the ideal design target.

[0084] Step 6: Use the controller to solve.

[0085] Finally, the controller u and the adaptive law obtained by adaptive scheduled time control (PPT) are combined. Introduced into the current loop closed loop and speed loop closed loop control of the brushless DC motor to improve the control performance. The introduction here refers to the PPT control algorithm (such as Figure 8 The PPT controller designed by the design process shown in steps 1 to 5 is written into the entire motor control process ( Figure 7 ) to represent Figure 7 The PPT section.

[0086] Specifically, hardware current sampling is used to acquire the motor's two-phase currents, ia and ib. The acquired currents are then transformed into iα and iβ using the Clark transform. A further Park transform is then performed to replace the rotating coordinate system information with the fixed coordinate system information, id and iq. This information, combined with the angle θ and angular velocity ω obtained by the speed sensor and the control target, is then input into the PPT control strategy. After these steps, the control variables Uq* and Ud* are obtained. These control variables are then input into the inverse Park transform to obtain the resolver coordinate information, Uα* and Uβ*. The SVPWM and inverter processes are then performed sequentially to ultimately control the BLDC motor and improve the system's performance.

[0087] In some embodiments, in step S130, the specific process of implementing closed-loop control of the motor by controlling the current loop and the speed loop using the predetermined time control model according to the operating parameters of the motor is described in the following exemplary embodiment.

[0088] The following combination Figure 3 The flowchart of an embodiment of the method of the present invention using the predetermined time control model to control the current loop and the speed loop is shown, further illustrating the specific process of using the predetermined time control model to control the current loop and the speed loop in step S130, including: steps S310 to S320.

[0089] Step S310 , in the closed-loop control of the motor, the predetermined time control model is introduced into both the current loop and the speed loop.

[0090] In step S320 , after introducing the predetermined time control model into both the current loop and the speed loop, closed-loop control of the motor is achieved by controlling the current loop and the speed loop according to the operating parameters of the motor.

[0091] In the solution of the present invention, an adaptive algorithm (i.e., the scheduled time control PPT algorithm) is used to compensate for unknown time-varying interference in the closed-loop control of the motor; at the same time, networked transmission is taken into consideration, and the time-varying parameters introduced during the networked transmission process are compensated, which has higher anti-interference performance and is conducive to improving the control accuracy of the motor.

[0092] In some embodiments, the current loop has a d-axis current portion and a q-axis current portion.

[0093] In step S310, the predetermined time control model is introduced into both the current loop and the speed loop, including: introducing the predetermined time control model into the speed loop to obtain a first PPT module; introducing the predetermined time control model into the d-axis current part of the current loop to obtain a second PPT module; and introducing the predetermined time control model into the q-axis current part of the current loop to obtain a third PPT module.

[0094] Below Figure 8 The controller designed Figure 7 The application of Three first-order systems with three control loops modeled independently.

[0095] First, the speed loop modeling and controller solution of the brushless DC motor:

[0096]

[0097] Among them, p n is the control gain, ψ f is the magnetic flux of the permanent magnet, B is the damping coefficient, J is the moment of inertia, ω is the angular velocity of the motor, T L is the motor torque. According to its state equation In the velocity loop there is z 11 =ω-ω r (acquisition and introduction of controlled quantities), (Introducing time-varying constraints), according to the above controller design method, the speed loop u1 can be obtained (solved to obtain the controller):

[0098]

[0099] Among them, m 11 =η 11 -δ 11 , μ 11 is η 11 The derived η 11 function term.

[0100] Adaptation rate where ξ 11 for and The matrix, r 11 , ρ 11 , K 11 and L 11 is the controller parameter, (1+τ) is the network transmission parameter, which is a common item. It can also be seen that u x The structures of (such as u1) are consistent and conform to the common formula.

[0101] Based on the above calculations As the output of PPT1 and the input of PPT3, the input and output descriptions here can be combined Figure 7 understand.

[0102] Second, brushless DC motor D-axis current loop modeling and controller solution:

[0103]

[0104] u2=u d

[0105]

[0106] For the d-axis current loop of the brushless DC motor, R s is the stator resistance of the motor, L d and L q are the inductances of the d-axis and q-axis respectively. According to their state equations, we have (acquisition and introduction of controlled quantities), (Introducing time-varying constraints), according to the above controller design method, it can be concluded that the speed loop u2 (solved to obtain the controller):

[0107]

[0108] Among them, m 12 =η 12 -δ 12 , μ 12 is η 12 The derived η 12 function term.

[0109] Adaptation rate where ξ 12 for and The matrix, r 12 , ρ 12 , K 12 and L 12 is the controller parameter; (1+τ) is the network transmission parameter. As input to the PARK inverse transform.

[0110] Third, brushless DC motor q-axis current loop modeling and controller solution:

[0111]

[0112] u3=u q

[0113]

[0114] For the q-axis current loop of the brushless DC motor, ψ ris the magnetic flux of the permanent magnet. According to its state equation, (acquisition and introduction of controlled quantities), (Introducing time-varying constraints), according to the above controller design method, it can be concluded that the speed loop u3 (solved to obtain the controller):

[0115]

[0116] where m 13 =η 13 -δ 13 , μ 13 is η 13 The derived η 13 function term.

[0117] Adaptation rate where ξ 13 for and The matrix, r 13 , ρ 13 , K 13 and L 13 is the controller parameter, (1+τ) is the network transmission parameter. Serves as the input for the inverse PARK transform. In addition, some of the symbols used to represent parameters have dots on them, indicating the derivative of the variable corresponding to the corresponding parameter.

[0118] In summary, the designed u (i.e. u1, u2, u3) is used to replace the U of PID (the control law of the traditional PID control method is U = kp*e1+ki*e2+kd*e3, where kp, ki and kd are proportional parameters respectively). The designed u has a higher anti-interference effect because the motor parameters and network transmission parameters are compensated using the designed adaptive rate. In the design process, the control accuracy and response speed can be artificially controlled through time-varying constraints, thereby improving the dynamic response speed of the system.

[0119] In the solution of the present invention, for arbitrary-order control systems, a control scheme of adaptive predetermined time control and networked control is adopted, and an adaptive compensation algorithm is used to process unknown time-varying interference in the system and simultaneously process the time-varying interference introduced by the networked control. The solution of the present invention processes the time-varying interference in the system through an adaptive predetermined time control method, and compensates for the nonlinear parameters introduced by the networked transmission, so as to achieve the purpose of improving the closed-loop control performance of the brushless DC motor. The predetermined time control strategy improves the system response speed and system accuracy by introducing time-varying constraints, and combines adaptive compensation to estimate the interference in the system operation and the time-varying problems introduced by the networked transmission, so that the system can obtain higher anti-interference. The solution of the present invention takes into account time-varying interference problems other than networking, and provides a high-order system control method to adapt to different application scenarios.

[0120] The present invention considers and compensates for the impact of networked transmission on control performance. Unlike the brushless DC motor closed-loop PID control schemes in related solutions, the present invention offers a higher dynamic response speed and allows for pre-setting of control performance independent of the motor's initial state. Through a designed adaptive estimation method (i.e., adaptive law), the present invention compensates for external interference and the system's inherent time-varying parameters, achieving superior anti-interference performance compared to the brushless DC motor closed-loop PID control methods in related solutions.

[0121] In some embodiments, the operating parameters of the motor include: a d-axis current id of the motor, a q-axis current iq of the motor, an angle θ of the motor, and an angular velocity ω of the motor.

[0122] In step S320, after the predetermined time control model is introduced into both the current loop and the speed loop, that is, when the speed loop has a first PPT module and the current loop has a second PPT module and a third PPT module, the specific process of closed-loop control of the motor is achieved by controlling the current loop and the speed loop according to the operating parameters of the motor. Please refer to the following exemplary description.

[0123] The following combination Figure 4 The flowchart of an embodiment of the method of the present invention for realizing closed-loop control of the motor by controlling the current loop and the speed loop is shown, further illustrating the specific process of realizing closed-loop control of the motor by controlling the current loop and the speed loop in step S320, including: steps S410 to S440.

[0124] In step S410, after the predetermined time control model is introduced into both the current loop and the speed loop, the angular velocity ω of the motor and the preset target angular velocity ω* of the motor are passed through the first PPT module in the speed loop to output the q-axis target current iq* of the motor.

[0125] Step S420 : In the d-axis current part of the current loop, the d-axis current id of the motor and the preset d-axis target current id* of the motor are passed through the second PPT module to output the d-axis reference voltage Ud* of the motor.

[0126] In step S430 , in the q-axis current portion of the current loop, the q-axis current iq of the motor and the q-axis target current iq* of the motor are passed through the third PPT module to obtain a q-axis reference voltage Uq* of the motor.

[0127] Step S440 , determining a control signal of the inverter side of the motor according to the angle θ of the motor, the d-axis reference voltage Ud* of the motor, and the q-axis reference voltage Uq* of the motor, so as to implement closed-loop control of the motor.

[0128] Figure 6 It is a structural diagram of an embodiment of a networked control system with adaptive scheduled time. Figure 6 It can display the closed-loop control process of the brushless DC motor. The sensor collects the phase current of the brushless DC motor, and after coordinate transformation processing, it is transmitted to the controller through network transmission for calculation with the target signal, and then the corresponding control information is output to the actuator through the network, ultimately achieving the goal of controlling the brushless DC motor.

[0129] in, Figure 6 The network shown here represents a data processing method. Both the sensor network and the actuator network represent data processing and transmission processes, but the details of the data processed differ. The sensor network is the means for acquiring and transmitting the motor's d-axis current id, the motor's q-axis current iq, the motor's angle θ (i.e., the motor's electrical angle), and the motor's angular velocity ω. The actuator network is responsible for transmitting control information.

[0130] Figure 7 The present invention is a structural diagram of an embodiment of a networked brushless DC motor vector control system based on adaptive scheduled time control. Figure 7 The final networked brushless DC motor vector control system structure diagram shows the overall structure after the algorithm of the last step in the embodiment is introduced. The PPT is a control strategy written according to the nature of the brushless DC motor application system itself, and its calculation method is given by Figure 8Steps 1 to 5 in the example shown are calculated and then the resulting control strategy is placed in the block diagram location shown to improve the overall performance of the motor control.

[0131] exist Figure 7 In the example shown, current sampling is used to acquire the two-phase currents ia and ib of a motor (such as a brushless DC motor (BLDC)). These currents are then transformed into currents iα and iβ using the Clark transform. The rotating coordinate system information (i.e., currents iα and iβ) is then transformed into fixed coordinate system information id and iq (i.e., d-axis current id and q-axis current iq) using a Park transform. This information, combined with the angle θ and angular velocity ω obtained by the motor's speed sensor and the control target, is then input into the PPT control strategy. The control target can be the target angular velocity ω*.

[0132] Specifically, the control target (such as the target angular velocity ω*) and the angular velocity ω are input into the first PPT module (i.e., PPT1) to generate the q-axis target current iq*. The q-axis target current iq* and the q-axis current iq are then input into the third PPT module (i.e., PPT3) to generate the q-axis reference voltage Uq*. The control target (such as the d-axis target current id*) and the d-axis current id are then input into the second PPT module (i.e., PPT2) to generate the d-axis reference voltage Ud*. The q-axis reference voltage Uq* and the d-axis reference voltage Ud* serve as the control variables. The first, third, and second PPT modules all operate using the PPT control strategy.

[0133] After the above steps, the control quantities Uq* and Ud* can be obtained, and then the obtained control quantities are input into the Park inverse transform to obtain the resolver coordinate information Uα* and Uβ*, and then the space vector pulse width modulation (SVPWM) and inverter process are performed in sequence to finally control the brushless DC motor BLDC and improve the operating performance of the brushless DC motor system.

[0134] The Clark transform converts the time-domain components of a three-phase system (in the abc coordinate system) into two components in an orthogonal stationary coordinate system (αβ coordinate system). The Park transform is a coordinate transformation method used to analyze the operation of synchronous motors. It converts physical quantities such as current and voltage in the three-phase stationary coordinate system (abc coordinate system) into the direct axis (d-axis) and quadrature axis (q-axis) coordinate systems that rotate with the rotor, thereby simplifying the motor mathematical model and achieving efficient control.

[0135] In the present invention, the control variable Uq* requires two PPT modules to obtain. This is related to the principle of motor control. After Park transformation, two detection data are obtained: the d-axis current id and the q-axis current iq. The d-axis current id causes motor heating, and the control goal is to make it equal to zero. In other words, the control variable Ud* will ultimately make the d-axis current id zero. During the control process, the difference between the monitoring data and 0 can be directly used as the control variable.

[0136] The control quantity Uq* is used to control the motor torque. Two PPT modules are required to obtain the control quantity Uq*. This is because: the first PPT module is used to process the ideal operating speed (i.e., the target angular velocity ω*) and the actual operating speed (such as the angular velocity ω), thereby obtaining the q-axis target current iq* and the detected q-axis current iq through the third PPT module to generate the control quantity Uq*, so two (two-loop control of the motor) or even more (such as in the three-loop control of the motor) are required.

[0137] The startup and operation of brushless DC motors inevitably involve interference, such as electromagnetic disturbances and temperature rise that degrade component performance, which can affect motor control accuracy. The present invention employs an adaptive algorithm (i.e., the Predicted Time Control (PPT) algorithm) to compensate for unknown, time-varying interference in closed-loop control. Furthermore, networked transmission is considered to compensate for time-varying parameters introduced during this process. Consequently, compared to other brushless DC motor closed-loop PID control schemes, the present invention exhibits superior interference resistance.

[0138] The brushless DC motor closed-loop PID control scheme in the related scheme corresponds to the brushless DC motor closed-loop PID control law: U = kp*e1+ki*e2+kd*e3, where kp, ki and kd are proportional constant, integral constant and differential constant respectively, e1, e2 and e3 are proportional error, integral error and differential error respectively, and the control effect is improved by adjusting kp, ki and kd. In contrast, the control strategy of the scheme of the present invention does not consider the influence of interference, and the response time T and control accuracy are improved. It's all out of control.

[0139] The technical solution of this embodiment is adopted. A controller and an adaptive law are designed according to an adaptive scheduled time control algorithm (i.e., a PPT control algorithm), and are introduced into the current loop closed-loop and speed loop closed-loop control of the brushless DC motor to compensate for unknown time-varying interference in the closed-loop control of the motor and time-varying interference introduced during network transmission. Specifically, a brushless DC motor control system model is constructed according to the application scenario of the brushless DC motor, the controlled quantity and time-varying constraints are introduced, coordinate transformation is performed, and the control law of the brushless DC motor control system model is solved to: design a controller and an adaptive law according to an adaptive scheduled time control algorithm (i.e., a PPT control algorithm) to compensate for unknown time-varying interference in the closed-loop control of the motor and time-varying interference introduced during network transmission. Thus, by utilizing the adaptive scheduled time control algorithm, unknown time-varying interference in the closed-loop control of the motor and time-varying interference introduced during network transmission are compensated, thereby improving the control accuracy of the motor.

[0140] According to an embodiment of the present invention, a motor control device corresponding to the motor control method is also provided. Figure 5 The closed-loop control system of the motor has a current loop and a speed loop; in the solution of the present invention, as shown in FIG. Figure 5 As shown, the motor control device includes: an acquisition unit 102 and a control unit 104.

[0141] The control unit 104 is configured to design a predetermined time control model for the closed-loop control of the motor in advance, so as to compensate for the time-varying interference in the closed-loop control of the motor; specifically, the predetermined time control model is designed according to the adaptive predetermined time control algorithm, such as the controller u and the control law corresponding to the predetermined time control PPT algorithm. The specific functions and processing of the control unit 104 are shown in step S110.

[0142] The acquisition unit 102 is configured to acquire operating parameters of the motor during closed-loop control of the motor, specifically, the motor's d-axis current id, the motor's q-axis current iq, the motor's angle θ, and the motor's angular velocity ω. The specific functions and processing of the acquisition unit 102 are described in step S120.

[0143] The control unit 104 is further configured to implement closed-loop control of the motor by controlling the current loop and the speed loop based on the operating parameters of the motor and using the predetermined time control model. The specific functions and processing of the control unit 104 are further described in step S130.

[0144] The solution of the present invention is to design an adaptive scheduled time control algorithm (i.e., scheduled time control PPT algorithm) to compensate for the time-varying interference encountered by the brushless DC motor during operation, thereby improving the accuracy of motor control. The closed-loop control of the brushless DC motor detects the information of the Q-axis phase-cut current (i.e., q-axis current) and the D-axis radial current (i.e., d-axis current) when the motor is running, and cooperates with the mechanical angle obtained by the position sensor to achieve precise position control. The algorithm is designed to compensate for the interference introduced by current acquisition and position information acquisition, thereby achieving higher accuracy and anti-interference of motor control. In addition, in order to better adapt to networked application scenarios, the time-varying parameter problem introduced by networked transmission has also been considered and compensated.

[0145] In some embodiments, the control unit 104 designs a predetermined time control model for the closed-loop control of the motor to compensate for time-varying interference in the closed-loop control of the motor, including:

[0146] The control unit 104 is further configured to construct a control system model of the motor, specifically a brushless DC motor control system model according to the application scenario of the brushless DC motor. The specific functions and processing of the control unit 104 are also shown in step S210.

[0147] The control unit 104 is further configured to introduce the controlled variable of the motor into the control system model of the motor based on the operating parameters of the motor, and to introduce adaptive estimated parameters of the motor based on the time-varying disturbance of the motor. The specific functions and processing of the control unit 104 are further described in step S220.

[0148] The control unit 104 is further configured to perform coordinate transformation based on the input controlled variable of the motor and the adaptive estimated parameters of the motor, and then use a command filter backstepping method to design a controller to obtain a controller for the motor control system model; and solve the adaptive law for the motor control system model. The specific functions and processing of the control unit 104 are further described in step S230.

[0149] The control unit 104 is further configured to use the controller of the motor control system model and the adaptive law of the motor control system model as the predetermined time control model to compensate for time-varying disturbances in the closed-loop control of the motor. The specific functions and processing of the control unit 104 are further described in step S240.

[0150] In the solution of the present invention, first, an adaptive law is designed to compensate for related interference and time-varying parameters, thereby improving the anti-interference ability of the motor; second, in order to obtain a faster dynamic response effect, a predetermined time control PPT algorithm is designed in the vector control to achieve a higher control effect; finally, the impact of networked transmission on control performance is also considered, and the time-varying parameters introduced in the networked transmission process are compensated.

[0151] In some embodiments, in the predetermined time control model, the controller and adaptive law of the motor control system model are expressed as follows:

[0152]

[0153] Where u is the controller, is an adaptive law, and The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of step n-1, m n is the difference between the command filter error and its compensation parameter, ρn represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

[0154] In the solution of the present invention, in order to compensate for the interference in the environment and the system itself in the above process, a control method with higher anti-interference and control accuracy is designed, that is, a predetermined time control PPT algorithm is designed. Figure 8 As shown in the example. Figure 8 As shown in FIG, the design process of the controller corresponding to the predetermined time control PPT algorithm includes the following steps:

[0155] Step 1: Model Construction: First, a brushless DC motor control system model is constructed based on the application scenario of the brushless DC motor. The system model used below is universally applicable to systems of any order. In the solution of the present invention, in order to enable the algorithm to be applied to any order, the system order is expanded to n dimensions, where n is a positive integer greater than or equal to 2. The system order is determined by the physical properties of the control system itself and is realized by representing the controlled system model as a mathematical model. In this case, it refers to the mathematical model determined by the physical properties of the control system in which the brushless DC motor is located.

[0156] Considering the network transmission (i.e. Figure 6The above brushless DC motor system can be summarized as follows:

[0157]

[0158] y=χ1 (1).

[0159] Where, and Represents the system status, Indicates control output. D i (t), and They represent unknown time-varying bounded parameters, unknown bounded external disturbances, known virtual control factors and known smooth functions (these functions are related to specific control systems). represents the derivative of the system state (the subscript refers to the state, and the value range of i has been given above), represents the nth system state (where n represents the system dimension / order), j i ( χ i ) represents the composite function of the first i system states, j n (χ) represents the composite function of all system states, χ i+1 represents the i+1th system variable, θ i and They represent the unknown bounded time-varying parameters and the known smooth function, D n (t) represents the unknown bounded external disturbance, χ1 represents the controlled signal and is also the first state variable of the system. q(u) is the quantized input of the system. is the controller to be designed. q(u) is the deformation of u during network transmission of the system. The final result of the solution of the present invention is q(u).

[0160] Step 2: Acquisition and introduction of controlled quantity.

[0161] z1(t)=y(t)-y r (t) represents the tracking error between the actual measurement value and the control expected value.

[0162] The controlled quantity acquisition here refers to the information obtained by sensors in motor control (such as Figure 7 The current information in the current sensor and the position information of the motor rotor obtained by the speed sensor) are then introduced into the calculation z1(t)=y(t)-y r(t), in our actual use, the formula will represent the difference between the desired motor current and the detected current, and also represent the difference between the desired motor stator angle and the actual detected angle, thereby introducing the controlled quantity into the calculation.

[0163] Step 3: Introduce time-varying constraints. To achieve the higher dynamic response speed mentioned in the solution of the present invention and allow for the preset control performance without relying on the initial state of the motor, it is necessary to introduce time-varying constraints. The specific steps for introducing time-varying constraints are: Introduce a time-varying constraint boundary Γ(t) to constrain the tracking error z1(t) between the actual measurement value and the control expectation value:

[0164]

[0165] Where, 0<T<∞ and They represent the controllable response time and steady-state control accuracy of the predefined system in steady state.

[0166] Formula (2) is the constraint boundary piecewise function introduced in the algorithm design. The first section of the function is used before reaching the artificially set steady-state time T, and the second section is used after reaching the artificially set steady-state time T. Among them, the response time T and the control accuracy They are all set artificially, t represents the running time of time, p represents a constant related to the system dimension / order, and the value range satisfies p satisfies 2p>n+1, and n is the order of the controlled system. Formula (2) uses a piecewise function: It is related to the algorithm advantages proposed by the system for the solution of the present invention. T represents the system stabilization time expected by the designer. The goal of using a piecewise function is to use the expected accuracy after T is reached. Constrain the overall error.

[0167] Step 4: Coordinate system transformation. Coordinate system transformation is a condition created to solve the final control law. The specific steps of coordinate system transformation are: relax the delay constraint boundary of -Γ(t)<z1<Γ(t) at the initial time, so that the constraint is infinite at the initial time, construct a composite function and map it to the interval (0,1]:

[0168]

[0169] Where c is the design parameter and λ(t) can be expressed as:

[0170]

[0171] The tracking error is finally converted to:

[0172]

[0173] Where h(λ(t)) represents the designed scaling function, λ(t) represents the function of the constraint bounds and the control error, c is the constant parameter to be adjusted by the designer, and b is a constant greater than 0 given by the designer. z1 and z1(t) both represent the tracking error between the actual measurement value and the control desired value.

[0174] Step 5: Solve the control law of the universal system model. The following is the calculation method and results:

[0175] Use command filter backstepping method to design controller and introduce coordinate transformation in, is α i The corresponding first-order command filter output, α i represents the virtual controller of step i, η i represents the error between the ith system state and the ith step virtual controller, χ i represents the i-th system state.

[0176] Among them, Y i is a design parameter, represents the command filter output of the i-th virtual controller, α i-1 represents the virtual controller at step i-1, represents the initial state of the filter output of the virtual controller command in step i, α i-1 (0) indicates the initial state of the virtual controller at step i-1. (Intermediate process)

[0177] Through compensation and calculation, the final controller and adaptive law can be calculated:

[0178]

[0179] Where u is the controller, For the adaptive law, yes The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of the n-1th step and the command filter error compensation parameters of the nth step, m n is the difference between the command filter error and its compensation parameter, ρ n represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

[0180] The coordinate transformation here is to simplify the calculation of the design process and avoid the generation of a large number of complex intermediate variables during the design process. It serves the final design goal of step 4. The final tracking error conversion in step 4 is the control purpose, which is to enable the control target to achieve the ideal design target.

[0181] Step 6: Use the controller to solve.

[0182] Finally, the controller u and the adaptive law obtained by adaptive scheduled time control (PPT) are combined. Introduced into the current loop closed loop and speed loop closed loop control of the brushless DC motor to improve the control performance. The introduction here refers to the PPT control algorithm (such as Figure 8 The PPT controller designed by the design process shown in steps 1 to 5 is written into the entire motor control process ( Figure 7 ) to represent Figure 7 The PPT section.

[0183] Specifically, hardware current sampling is used to acquire the motor's two-phase currents, ia and ib. The acquired currents are then transformed into iα and iβ using the Clark transform. A further Park transform is then performed to replace the rotating coordinate system information with the fixed coordinate system information, id and iq. This information, combined with the angle θ and angular velocity ω obtained by the speed sensor and the control target, is then input into the PPT control strategy. After these steps, the control variables Uq* and Ud* are obtained. These control variables are then input into the inverse Park transform to obtain the resolver coordinate information, Uα* and Uβ*. The SVPWM and inverter processes are then performed sequentially to ultimately control the BLDC motor and improve the system's performance.

[0184] In some embodiments, the control unit 104 implements closed-loop control of the motor by controlling the current loop and the speed loop based on the operating parameters of the motor using the predetermined time control model, including:

[0185] The control unit 104 is further configured to introduce the predetermined time control model into both the current loop and the speed loop in the closed-loop control of the motor. Specific functions and processing of the control unit 104 are also described in step S310.

[0186] The control unit 104 is further configured to implement closed-loop control of the motor by controlling the current loop and the speed loop according to the operating parameters of the motor after introducing the predetermined time control model into both the current loop and the speed loop. The specific functions and processing of the control unit 104 are further described in step S320.

[0187] In the solution of the present invention, an adaptive algorithm (i.e., the scheduled time control PPT algorithm) is used to compensate for unknown time-varying interference in the closed-loop control of the motor; at the same time, networked transmission is taken into consideration, and the time-varying parameters introduced during the networked transmission process are compensated, which has higher anti-interference performance and is conducive to improving the control accuracy of the motor.

[0188] In some embodiments, the current loop has a d-axis current portion and a q-axis current portion.

[0189] The control unit 104 introduces the predetermined time control model into both the current loop and the speed loop, including: the control unit 104 is specifically configured to introduce the predetermined time control model into the speed loop to obtain a first PPT module; introduce the predetermined time control model into the d-axis current part of the current loop to obtain a second PPT module; and introduce the predetermined time control model into the q-axis current part of the current loop to obtain a third PPT module.

[0190] Below Figure 8 The controller designed Figure 7 The application of Three first-order systems with three control loops modeled independently.

[0191] First, the speed loop modeling and controller solution of the brushless DC motor:

[0192]

[0193] Among them, p n is the control gain, ψ f is the magnetic flux of the permanent magnet, B is the damping coefficient, J is the moment of inertia, ω is the angular velocity of the motor, T L is the motor torque. According to its state equation In the velocity loop there is z 11 =ω-ω r (acquisition and introduction of controlled quantities), (Introducing time-varying constraints), according to the above controller design method, the speed loop u1 can be obtained (solved to obtain the controller):

[0194]

[0195] Among them, m 11 =η 11 -δ 11 , μ 11 is η 11 The derived η 11 function term.

[0196] Adaptation rate where ξ 11 for and The matrix, r 11 , ρ 11 , K 11 and L 11 is the controller parameter, (1+τ) is the network transmission parameter, which is a common item. It can also be seen that u x The structures of (such as u1) are consistent and conform to the common formula.

[0197] Based on the above calculations As the output of PPT1 and the input of PPT3, the input and output descriptions here can be combined Figure 7 understand.

[0198] Second, brushless DC motor D-axis current loop modeling and controller solution:

[0199]

[0200] u2=u d

[0201]

[0202] For the d-axis current loop of the brushless DC motor, R s is the stator resistance of the motor, L d and L q are the inductances of the d-axis and q-axis respectively. According to their state equations, we have (acquisition and introduction of controlled quantities), (Introducing time-varying constraints), according to the above controller design method, it can be concluded that the speed loop u2 (solved to obtain the controller):

[0203]

[0204] Among them, m 12 =η 12 -δ 12 , μ 12 is η 12 The derived η 12 function term.

[0205] Adaptation rate where ξ 12 for and The matrix, r 12 , ρ 12 , K 12 and L 12 is the controller parameter; (1+τ) is the network transmission parameter. As input to the PARK inverse transform.

[0206] Third, brushless DC motor q-axis current loop modeling and controller solution:

[0207]

[0208] u3=u q

[0209]

[0210] For the q-axis current loop of the brushless DC motor, ψ r is the magnetic flux of the permanent magnet. According to its state equation, (acquisition and introduction of controlled quantities), (Introducing time-varying constraints), according to the above controller design method, it can be concluded that the speed loop u3 (solved to obtain the controller):

[0211]

[0212] where m 13 =η 13 -δ 13 , μ 13 is η 13 The derived η 13 function term.

[0213] Adaptation rate where ξ 13 for and The matrix, r 13 , ρ 13 , K 13 and L 13 is the controller parameter, (1+τ) is the network transmission parameter. Serves as the input for the inverse PARK transform. In addition, some of the symbols used to represent parameters have dots on them, indicating the derivative of the variable corresponding to the corresponding parameter.

[0214] In summary, the designed u (i.e. u1, u2, u3) is used to replace the U of PID (the control law of the traditional PID control method is U = kp*e1+ki*e2+kd*e3, where kp, ki and kd are proportional parameters respectively). The designed u has a higher anti-interference effect because the motor parameters and network transmission parameters are compensated using the designed adaptive rate. In the design process, the control accuracy and response speed can be artificially controlled through time-varying constraints, thereby improving the dynamic response speed of the system.

[0215] In the solution of the present invention, for arbitrary-order control systems, a control scheme of adaptive predetermined time control and networked control is adopted, and an adaptive compensation algorithm is used to process unknown time-varying interference in the system and simultaneously process the time-varying interference introduced by the networked control. The solution of the present invention processes the time-varying interference in the system through an adaptive predetermined time control method, and compensates for the nonlinear parameters introduced by the networked transmission, so as to achieve the purpose of improving the closed-loop control performance of the brushless DC motor. The predetermined time control strategy improves the system response speed and system accuracy by introducing time-varying constraints, and combines adaptive compensation to estimate the interference in the system operation and the time-varying problems introduced by the networked transmission, so that the system can obtain higher anti-interference. The solution of the present invention takes into account time-varying interference problems other than networking, and provides a high-order system control method to adapt to different application scenarios.

[0216] The present invention considers and compensates for the impact of networked transmission on control performance. Unlike the brushless DC motor closed-loop PID control schemes in related solutions, the present invention offers a higher dynamic response speed and allows for pre-setting of control performance independent of the motor's initial state. Through a designed adaptive estimation method (i.e., adaptive law), the present invention compensates for external interference and the system's inherent time-varying parameters, achieving superior anti-interference performance compared to the brushless DC motor closed-loop PID control methods in related solutions.

[0217] In some embodiments, the operating parameters of the motor include: a d-axis current id of the motor, a q-axis current iq of the motor, an angle θ of the motor, and an angular velocity ω of the motor.

[0218] The control unit 104, after introducing the predetermined time control model into both the current loop and the speed loop, i.e., when the speed loop has a first PPT module and the current loop has a second PPT module and a third PPT module, implements closed-loop control of the motor by controlling the current loop and the speed loop according to the operating parameters of the motor, including:

[0219] The control unit 104 is further configured to, after introducing the predetermined time control model into both the current loop and the speed loop, output the motor's q-axis target current iq* in the speed loop after passing the motor's angular velocity ω and a preset target angular velocity ω* through the first PPT module. The specific functions and processing of the control unit 104 are further described in step S410.

[0220] The control unit 104 is further configured to, in the d-axis current portion of the current loop, transmit the motor's d-axis current id and a preset d-axis target current id* to the second PPT module, and output a d-axis reference voltage Ud* for the motor. The specific functions and processing of the control unit 104 are further described in step S420.

[0221] The control unit 104 is further configured to obtain a q-axis reference voltage Uq* of the motor by passing the q-axis current iq and the q-axis target current iq* of the motor through the third PPT module in the q-axis current portion of the current loop. The specific functions and processing of the control unit 104 are further described in step S430.

[0222] The control unit 104 is further configured to determine a control signal for the motor inverter based on the motor angle θ, the motor's d-axis reference voltage Ud*, and the motor's q-axis reference voltage Uq*, thereby implementing closed-loop control of the motor. The specific functions and processing of the control unit 104 are further described in step S440.

[0223] Figure 6 It can display the closed-loop control process of the brushless DC motor. The sensor collects the phase current of the brushless DC motor, and after coordinate transformation processing, it is transmitted to the controller through network transmission for calculation with the target signal, and then the corresponding control information is output to the actuator through the network, ultimately achieving the goal of controlling the brushless DC motor.

[0224] in, Figure 6 The network shown here represents a data processing method. Both the sensor network and the actuator network represent data processing and transmission processes, but the details of the data processed differ. The sensor network is the means for acquiring and transmitting the motor's d-axis current id, the motor's q-axis current iq, the motor's angle θ (i.e., the motor's electrical angle), and the motor's angular velocity ω. The actuator network is responsible for transmitting control information.

[0225] Figure 7 The final networked brushless DC motor vector control system structure diagram shows the overall structure after the algorithm of the last step in the embodiment is introduced. The PPT is a control strategy written according to the nature of the brushless DC motor application system itself, and its calculation method is given by Figure 8 Steps 1 to 5 in the example shown are calculated and then the resulting control strategy is placed in the block diagram location shown to improve the overall performance of the motor control.

[0226] exist Figure 7In the example shown, current sampling is used to acquire the two-phase currents ia and ib of a motor (such as a brushless DC motor (BLDC)). These currents are then transformed into currents iα and iβ using the Clark transform. The rotating coordinate system information (i.e., currents iα and iβ) is then transformed into fixed coordinate system information id and iq (i.e., d-axis current id and q-axis current iq) using a Park transform. This information, combined with the angle θ and angular velocity ω obtained by the motor's speed sensor and the control target, is then input into the PPT control strategy. The control target can be the target angular velocity ω*.

[0227] Specifically, the control target (such as the target angular velocity ω*) and the angular velocity ω are input into the first PPT module (i.e., PPT1) to generate the q-axis target current iq*. The q-axis target current iq* and the q-axis current iq are then input into the third PPT module (i.e., PPT3) to generate the q-axis reference voltage Uq*. The control target (such as the d-axis target current id*) and the d-axis current id are then input into the second PPT module (i.e., PPT2) to generate the d-axis reference voltage Ud*. The q-axis reference voltage Uq* and the d-axis reference voltage Ud* serve as the control variables. The first, third, and second PPT modules all operate using the PPT control strategy.

[0228] After the above steps, the control quantities Uq* and Ud* can be obtained, and then the obtained control quantities are input into the Park inverse transform to obtain the resolver coordinate information Uα* and Uβ*, and then the space vector pulse width modulation (SVPWM) and inverter process are performed in sequence to finally control the brushless DC motor BLDC and improve the operating performance of the brushless DC motor system.

[0229] The Clark transform converts the time-domain components of a three-phase system (in the abc coordinate system) into two components in an orthogonal stationary coordinate system (αβ coordinate system). The Park transform is a coordinate transformation method used to analyze the operation of synchronous motors. It converts physical quantities such as current and voltage in the three-phase stationary coordinate system (abc coordinate system) into the direct axis (d-axis) and quadrature axis (q-axis) coordinate systems that rotate with the rotor, thereby simplifying the motor mathematical model and achieving efficient control.

[0230] In the present invention, the control variable Uq* requires two PPT modules to obtain. This is related to the principle of motor control. After Park transformation, two detection data are obtained: the d-axis current id and the q-axis current iq. The d-axis current id causes motor heating, and the control goal is to make it equal to zero. In other words, the control variable Ud* will ultimately make the d-axis current id zero. During the control process, the difference between the monitoring data and 0 can be directly used as the control variable.

[0231] The control quantity Uq* is used to control the motor torque. Two PPT modules are required to obtain the control quantity Uq*. This is because: the first PPT module is used to process the ideal operating speed (i.e., the target angular velocity ω*) and the actual operating speed (such as the angular velocity ω), thereby obtaining the q-axis target current iq* and the detected q-axis current iq through the third PPT module to generate the control quantity Uq*, so two (two-loop control of the motor) or even more (such as in the three-loop control of the motor) are required.

[0232] The startup and operation of brushless DC motors inevitably involve interference, such as electromagnetic disturbances and temperature rise that degrade component performance, which can affect motor control accuracy. The present invention employs an adaptive algorithm (i.e., the Predicted Time Control (PPT) algorithm) to compensate for unknown, time-varying interference in closed-loop control. Furthermore, networked transmission is considered to compensate for time-varying parameters introduced during this process. Consequently, compared to other brushless DC motor closed-loop PID control schemes, the present invention exhibits superior interference resistance.

[0233] The brushless DC motor closed-loop PID control scheme in the related scheme corresponds to the brushless DC motor closed-loop PID control law: U = kp*e1+ki*e2+kd*e3, where kp, ki and kd are proportional constant, integral constant and differential constant respectively, e1, e2 and e3 are proportional error, integral error and differential error respectively, and the control effect is improved by adjusting kp, ki and kd. In contrast, the control strategy of the scheme of the present invention does not consider the influence of interference, and the response time T and control accuracy are improved. It's all out of control.

[0234] Since the processing and functions implemented by the device of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned method, for any details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments and will not be repeated here.

[0235] According to an embodiment of the present invention, a motor corresponding to the motor control device is also provided. The motor may include: the motor control device described above.

[0236] Since the processing and functions implemented by the motor of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned device, for any details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments and will not be repeated here.

[0237] According to an embodiment of the present invention, a computer program product corresponding to the motor control method is further provided, comprising a computer program. When the computer program is executed by a processor, the steps of the motor control method described above are implemented.

[0238] Since the processing and functions implemented by the product of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned method, for any details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments and will not be repeated here.

[0239] According to an embodiment of the present invention, a storage medium corresponding to the motor control method is also provided, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the steps of the motor control method described above.

[0240] Since the processing and functions implemented by the storage medium of this embodiment basically correspond to the embodiments, principles and examples of the aforementioned method, for any details not fully described in this embodiment, please refer to the relevant descriptions in the aforementioned embodiments and will not be repeated here.

[0241] In summary, it is easy for those skilled in the art to understand that, under the premise of no conflict, the above-mentioned advantageous methods can be freely combined and superimposed.

[0242] The foregoing description is merely an embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of the claims.

Claims

1. A method for controlling a motor, characterized in that: The closed-loop control system of the motor has a current loop and a speed loop; the control method of the motor includes: Designing a predetermined time control model for the closed-loop control of the motor to compensate for time-varying interference in the closed-loop control of the motor; In the closed-loop control of the motor, obtaining operating parameters of the motor; According to the operating parameters of the motor, the predetermined time control model is used to control the current loop and the speed loop to achieve closed-loop control of the motor.

2. The motor control method according to claim 1, characterized in that: For the closed-loop control of the motor, a predetermined time control model is designed to compensate for time-varying interference in the closed-loop control of the motor, including: Constructing a control system model of the motor; In the control system model of the motor, based on the operating parameters of the motor, the controlled variable of the motor is introduced; and based on the time-varying interference of the motor, the adaptive estimation parameters of the motor are introduced; Based on the controlled quantity of the motor and the adaptive estimated parameters of the motor, after coordinate transformation, a controller is designed using a command filter backstepping method to obtain a controller of the motor control system model; and an adaptive law of the motor control system model is obtained by solving the controller. The controller of the motor control system model and the adaptive law of the motor control system model are used as the predetermined time control model to compensate for time-varying disturbances in the closed-loop control of the motor.

3. The motor control method according to claim 2, characterized in that: In the predetermined time control model, the controller and adaptive law of the motor control system model are expressed as follows: Where u is the controller, is an adaptive law, and The derivative of r n , K n and L n are all design parameters, ι is a network parameter, η n is the command filtering error, δ n-1 and δ n They are the command filter error compensation parameters of step n-1, m n is the difference between the command filter error and its compensation parameter, ρn represents the positive bounded time-varying function designed by the designer based on the control system model of the motor, ψ n ,ξ n All represent intermediate functions, and the subscript n represents the system order.

4. The method for controlling a motor according to any one of claims 1 to 3, characterized in that: According to the operating parameters of the motor, using the predetermined time control model, by controlling the current loop and the speed loop, closed-loop control of the motor is achieved, including: In the closed-loop control of the motor, the predetermined time control model is introduced into both the current loop and the speed loop; According to the operating parameters of the motor, closed-loop control of the motor is achieved by controlling the current loop and the speed loop.

5. The motor control method according to claim 4, characterized in that: The current loop has a d-axis current part and a q-axis current part; The predetermined time control model is introduced into both the current loop and the speed loop, including: In the speed loop, the predetermined time control model is introduced to obtain a first PPT module; The predetermined time control model is introduced into the d-axis current part of the current loop to obtain a second PPT module; and the predetermined time control model is introduced into the q-axis current part of the current loop to obtain a third PPT module.

6. The motor control method according to claim 4 or 5, characterized in that: The operating parameters of the motor include: the d-axis current id of the motor, the q-axis current iq of the motor, the angle θ of the motor, and the angular velocity ω of the motor; In a case where the speed loop has a first PPT module and the current loop has a second PPT module and a third PPT module, closed-loop control of the motor is achieved by controlling the current loop and the speed loop according to operating parameters of the motor, including: In the speed loop, the angular velocity ω of the motor and the preset target angular velocity ω* of the motor are passed through the first PPT module to output the q-axis target current iq* of the motor; In the d-axis current part of the current loop, the d-axis current id of the motor and the preset d-axis target current id* of the motor are passed through the second PPT module to output the d-axis reference voltage Ud* of the motor; In the q-axis current part of the current loop, the q-axis current iq of the motor and the q-axis target current iq* of the motor are passed through the third PPT module to obtain the q-axis reference voltage Uq* of the motor; A control signal on the inverter side of the motor is determined according to the angle θ of the motor, the d-axis reference voltage Ud* of the motor, and the q-axis reference voltage Uq* of the motor to achieve closed-loop control of the motor.

7. A motor control device, characterized in that: The closed-loop control system of the motor has a current loop and a speed loop; the control device of the motor includes: a control unit configured to design a predetermined time control model for the closed-loop control of the motor, so as to compensate for time-varying interference in the closed-loop control of the motor; an acquiring unit, configured to acquire operating parameters of the motor in closed-loop control of the motor; The control unit is further configured to implement closed-loop control of the motor by controlling the current loop and the speed loop using the predetermined time control model according to the operating parameters of the motor.

8. A motor, characterized in that: include: The motor control device according to claim 7.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the motor control method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the motor control method according to any one of claims 1 to 6 are implemented.

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