Controller design method, device and equipment of permanent magnet synchronous motor and storage medium

Abstract

The application discloses a permanent magnet synchronous motor controller design method and device, equipment and storage medium, relates to the permanent magnet synchronous motor technical field, the method includes establishing the nonlinear mathematical model of the permanent magnet synchronous motor, the nonlinear mathematical model is used for determining the parameter condition of chaotic oscillation;The nonlinear mathematical model is linearized based on the preset fuzzy rule processing, and a global fuzzy system model is obtained;Through the global fuzzy system model, a sliding mode surface including a current state error and a historical state error cumulative term is generated, and the sliding mode surface is used to define a convergence path;A sliding mode controller is generated based on the sliding mode surface, and the sliding mode controller includes a time-varying gain term associated with a preset convergence time, so that the system state variable converges to an equilibrium point within the preset convergence time. The application has the effect of realizing the specified time stabilization of the permanent magnet synchronous motor with time delay and chaotic characteristics.

Description

Technical Field

[0001] This application relates to the field of permanent magnet synchronous motor technology, and in particular to a controller design method, device, equipment and storage medium for a permanent magnet synchronous motor. Background Technology

[0002] For the control of permanent magnet synchronous motors, relevant control schemes include asymptotic stability control, finite-time and fixed-time control, and sliding mode control. Asymptotic stability control, based on asymptotic stability theory, requires the system state variables to converge to the equilibrium point only when time approaches infinity. However, chaotic oscillations in the motor need to be effectively eliminated within a finite time; the convergence time of the asymptotic stability method is too long, failing to meet real-time control requirements. Finite-time and fixed-time control methods offer faster convergence speeds and higher steady-state accuracy compared to asymptotic stability methods, but their convergence time heavily depends on initial system conditions or system parameters. When the initial state of the motor is unknown or system parameters are difficult to obtain accurately, control performance will be affected, failing to achieve the expected control objectives. Sliding mode control has strong robustness and anti-interference capabilities; however, existing sliding mode control methods are mainly designed for time-delay-free systems, neglecting time-varying delays such as signal transmission delays and inverter delays commonly found in motor systems. Summary of the Invention

[0003] The purpose of this application is to at least solve one of the technical problems existing in the prior art, and to provide a controller design method, device, equipment and storage medium for permanent magnet synchronous motors, which aims to achieve time-delayed stabilization of permanent magnet synchronous motors with time delay and chaotic characteristics.

[0004] In a first aspect, embodiments of this application provide a controller design method for a permanent magnet synchronous motor, comprising: A nonlinear mathematical model of the permanent magnet synchronous motor is established, and the nonlinear mathematical model is used to determine the parameter conditions for chaotic oscillation. The nonlinear mathematical model is linearized based on preset fuzzy rules to obtain a global fuzzy system model. The global fuzzy system model generates a sliding surface that includes the current state error and the cumulative term of the historical state error. The sliding surface is used to define the convergence path. A sliding mode controller is generated based on the sliding surface. The sliding mode controller includes a time-varying gain term associated with a preset convergence time, so that the system state variables converge to the equilibrium point within the preset convergence time.

[0005] The technical solution according to the embodiments of this application has at least the following beneficial effects: By using a specified-time sliding mode controller including a preset convergence time parameter, and introducing a time-varying gain term related to the preset time into the controller, the system state can be forced to converge from the chaotic state to the equilibrium point within a preset total time, thus overcoming the theoretical limitation that the time of the asymptotic stability method tends to infinity. Furthermore, since the time to reach the sliding surface and the time to converge to the equilibrium point are independent of the initial system state and depend only on the preset time parameter during design, the system can still stabilize within the same specified time, achieving complete decoupling of the convergence time from the initial state and parameters; the historical state error accumulation term in the sliding surface can effectively compensate for the adverse effects of time delay on system stability.

[0006] According to some embodiments of this application, establishing the nonlinear mathematical model of the permanent magnet synchronous motor includes: Establish the state equation of the permanent magnet synchronous motor, and set a time-varying delay term to characterize the signal transmission delay or system response delay in the state equation to obtain a set of time-varying delay differential equations. By adjusting the time-varying time-delay differential equations with preset chaotic oscillation parameters, a nonlinear mathematical model with time-delay and chaotic characteristics is obtained.

[0007] According to some embodiments of this application, the linearization process of the nonlinear mathematical model based on preset fuzzy rules to obtain a global fuzzy system model includes: Determine the value range of any state variable of the permanent magnet synchronous motor, divide the value range into multiple fuzzy sets, and set corresponding fuzzy rules for each fuzzy set; Based on the dynamic parameters under each of the fuzzy rules, the corresponding linear state-space model is obtained; By weighting and combining the outputs of each linear state-space model using a preset membership function, a global fuzzy system model is obtained.

[0008] According to some embodiments of this application, generating a sliding surface including the current state error and the cumulative term of historical state error through the global fuzzy system model includes: Based on the global fuzzy system model, the current state error term is obtained, and the historical state error accumulation term is obtained by nonlinearly weighting and accumulating the historical state errors. A sliding surface is generated using the current state error and the accumulated historical state error.

[0009] According to some embodiments of this application, the sliding mode controller includes an equivalent control module and a switching control module; The equivalent control module is used to offset the current dynamic parameters of the permanent magnet synchronous motor so that the state parameters of the permanent magnet synchronous motor approach the sliding surface; the switching control module includes a time-varying gain term associated with a preset convergence time, which is used to monotonically increase during the control process as the time approaches the preset convergence time so that the state parameters of the permanent magnet synchronous motor reach the sliding surface within the preset convergence time.

[0010] According to some embodiments of this application, the time-varying gain term is obtained by the difference between a preset convergence time and the current time; the time-varying gain term includes a nonlinear term related to the sliding surface, which is used to adjust the control intensity at different stages.

[0011] According to some embodiments of this application, it also includes: The stability of the sliding mode controller is verified using preset stability verification rules.

[0012] Secondly, embodiments of this application provide an operation control device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the controller design method for the permanent magnet synchronous motor described in the first aspect.

[0013] Thirdly, embodiments of this application provide an electronic device including the operation control device described in the second aspect above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which are used to cause a computer to execute the controller design method for a permanent magnet synchronous motor as described in the first aspect above.

[0015] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0016] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0017] The present application will be further described below with reference to the accompanying drawings and embodiments.

[0018] Figure 1 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in one embodiment of this application; Figure 2This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; Figure 3 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; Figure 4 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; Figure 5 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; Figure 6 This is a phase trajectory diagram of a permanent magnet synchronous motor system provided in another embodiment of this application; Figure 7 This is a system state trajectory diagram of a simulated permanent magnet synchronous motor system without control, provided in another embodiment of this application; Figure 8 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application; Figure 9 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application; Figure 10 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application; Figure 11 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application; Figure 12 This is a schematic diagram of an operation control device for implementing a controller design method for a permanent magnet synchronous motor, provided in one embodiment of this application. Detailed Implementation

[0019] This section will describe in detail the specific embodiments of this application. Preferred embodiments of this application are shown in the accompanying drawings. The purpose of the drawings is to supplement the textual description with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of this application, but they should not be construed as limiting the scope of protection of this application.

[0020] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0021] In the description of this application, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is for the purpose of distinguishing technical features only and should not be construed as indicating or implying relative importance, nor as implying or specifying the number of indicated technical features, nor as implying or specifying the sequential relationship of the indicated technical features.

[0022] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0023] The following description, in conjunction with the accompanying drawings, further elaborates on various embodiments of the controller design method for the permanent magnet synchronous motor of this application.

[0024] like Figure 1 As shown, Figure 1 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in one embodiment of this application. The controller design method for the permanent magnet synchronous motor may include, but is not limited to, steps S110, S120, S130 and S140.

[0025] Step S110: Establish a nonlinear mathematical model of the permanent magnet synchronous motor. The nonlinear mathematical model is used to determine the parameter conditions for chaotic oscillation. Step S120: Linearize the nonlinear mathematical model based on preset fuzzy rules to obtain a global fuzzy system model; Step S130: Generate a sliding surface that includes the current state error and the cumulative term of the historical state error through the global fuzzy system model. The sliding surface is used to define the convergence path. Step S140: Generate a sliding mode controller based on the sliding mode surface. The sliding mode controller includes a time-varying gain term associated with a preset convergence time, so that the system state variables converge to the equilibrium point within the preset convergence time.

[0026] It is understandable that a permanent magnet synchronous motor (PMSM) is a multivariable, strongly coupled nonlinear system, whose dynamic behavior is described by voltage equations, flux linkage equations, and motion equations. In the rotating dq coordinate system, the state variables of the PMSM include the stator d-axis current, q-axis current, and rotor angular velocity, which have product terms, leading to nonlinear characteristics. Signal transmission delay, inverter dead-time effect, and digital controller computation time introduce time-varying delays, further complicating the dynamics of the PMSM system. Therefore, the PMSM controller design method provided in this application can address PMSM systems prone to chaotic oscillations due to time delays and nonlinear factors, enabling pre-setting of convergence time without relying on the initial state. For example, the PMSM controller design method provided in this application can establish an accurate nonlinear mathematical model, perform linearization using fuzzy rules, generate a sliding mode surface including historical state information, and produce a sliding mode controller with time-varying gain. Ultimately, this achieves system state convergence to the equilibrium point within a specified time, effectively suppressing chaotic phenomena and improving the motor's dynamic response speed and robustness.

[0027] For example, by selecting specific parameters of a permanent magnet synchronous motor (PMSM) system, such as motor inductance, resistance, moment of inertia, and permanent magnet flux linkage, the dynamic behavior of the PMSM system under different parameter combinations can be analyzed. When the parameters fall within certain specific ranges, the PMSM system will exhibit chaotic oscillations, leading to unstable motor operation, increased torque pulsation, aggravated noise, and system runaway. Therefore, the nonlinear mathematical model is used to determine the parameter conditions that induce chaotic oscillations, providing a basis for the subsequent controller design and ensuring that the controller can effectively suppress chaotic states.

[0028] After establishing a nonlinear mathematical model, directly applying it to controller design would be extremely complex and difficult to solve analytically. Therefore, pre-defined fuzzy rules, such as the Takagi-Sugeno (TS) fuzzy method, can be used to achieve a linear approximation of the nonlinear system. For example, the TS fuzzy method divides the working space of the nonlinear system into several fuzzy regions. Within each region, a linear model is used to approximate the original nonlinear system. Then, membership functions are used to combine the local linear models to form a global fuzzy system model. Specifically, firstly, one or more state variables are selected as fuzzy premise variables. For example, rotational speed or current is selected as the dividing criterion and its range of variation is determined. Then, this range is divided into several fuzzy sets, each corresponding to an IF-THEN fuzzy rule. For example, rule 1 states that if the rotational speed is low, the dynamics of the permanent magnet synchronous motor system are approximated by a linear model A1; rule 2 states that if the rotational speed is high, the dynamics of the permanent magnet synchronous motor system are approximated by a linear model A2. Each local linear model is in the form of a state-space expression. The system matrix is ​​obtained by linearizing the original nonlinear equations near the corresponding operating point. The membership function describes the degree to which the current state belongs to each fuzzy set, and can use triangular, Gaussian, or trapezoidal functions. The output of the global fuzzy system model is equal to the weighted sum of the outputs of all local linear models, and the weights are the membership degrees of the corresponding rules. In this way, complex nonlinear problems can be transformed into combinations of multiple linear problems, greatly reducing the mathematical complexity of controller design. On the other hand, since the TS fuzzy model can approximate the original nonlinear system with arbitrary precision, the controller designed based on this model can still maintain good control performance in practical applications and is suitable for chaotic permanent magnet synchronous motor systems with strong nonlinearity and time delay characteristics.

[0029] For example, sliding mode control is a nonlinear robust control method. It involves designing a sliding surface and applying control to drive the permanent magnet synchronous motor system from an arbitrary initial position onto the sliding surface, where it then slides to an equilibrium point. The sliding surface design provided in this application differs from that based solely on the current state error; instead, it includes a cumulative term of historical state errors, i.e., an integral term or a memory term. Thus, due to time delays, the current control action requires a certain period to affect the system output, while the cumulative term of historical state errors reflects the degree to which the system deviates from the desired trajectory over a past period, thereby compensating for the effects of delays in advance within the control law. For instance, a sliding surface can be defined as a linear combination of state variables plus a nonlinear integral term, including the error between the current state and the desired value. The function in the integral term can be designed in a nonlinear form to accelerate convergence or improve dynamic quality. In the sliding surface provided in the embodiments of this application, the sliding surface is used to define the ideal convergence path of the permanent magnet synchronous motor system state. When the system state reaches the sliding surface, the subsequent dynamic behavior will be determined by the equation of the sliding surface itself, and will not be affected by the perturbation of the original system parameters and external disturbances, thereby ensuring the robustness of the system. At the same time, since the integral term contains historical information, the motion of the permanent magnet synchronous motor system on the sliding surface can naturally compensate for the time delay effect, making the convergence process smoother and more reliable.

[0030] For example, a sliding mode controller is generated based on the aforementioned sliding surface. This controller includes a time-varying gain term associated with a preset convergence time to ensure that the system state variables converge to an equilibrium point within the preset time. In other words, the sliding mode controller improved in this embodiment allows the convergence time to be pre-specified through the time-varying gain term, and it is independent of the system's initial state and parameters. This differs from typical sliding mode control, which can only guarantee asymptotic or finite-time convergence. For example, the time-varying gain term is based on a specified time stability theory, setting a gain in the controller that monotonically increases with time and tends to infinity at a preset time, thereby forcing the permanent magnet synchronous motor system to complete convergence before the preset time point.

[0031] Based on this, the controller design method for permanent magnet synchronous motors provided in this application analyzes the chaotic characteristics and time delay effects of permanent magnet synchronous motors through nonlinear mathematical modeling, and then uses a preset fuzzy method to transform the complex nonlinear model into a linear combination form that is easy to process. Then, a sliding mode surface with historical error accumulation is designed, and a sliding mode controller with time-varying gain is generated through the sliding mode surface to force the permanent magnet synchronous motor system state to converge before a specified time.

[0032] For example, firstly, based on the actual physical parameters of the motor, including stator resistance, dq-axis inductance, permanent magnet flux linkage, moment of inertia, and viscous friction coefficient, a nonlinear mathematical model in the form of a system of differential equations needs to be established. The parameter range where chaos occurs in the system is determined through experiments or simulations. Then, appropriate state variables are selected as fuzzy premise variables to divide the universe of discourse and membership functions are designed. A global fuzzy system model is obtained through the TS fuzzy rule. This model consists of several local linear state equations and corresponding membership functions, accurately describing the dynamic behavior of the original system in the chaotic region. Subsequently, a sliding mode surface is designed based on this fuzzy model. The historical error accumulation term can be designed as an integral form or a nonlinear functional. For example, a nonlinear function related to a preset convergence time can be set to achieve convergence at a specified time. The sliding mode controller is designed based on the equivalent control principle and the reaching law method to ensure that the time-varying gain term is integrated into the control law, avoiding chattering caused by sudden gain changes. During controller parameter tuning, the preset time and other adjustment parameters need to be reasonably selected based on the actual system's response speed and allowable control amplitude to achieve the optimal control effect.

[0033] It is understood that the controller design method for permanent magnet synchronous motors provided in this application embodiment realizes the pre-setting of the convergence time, making the time for the motor to recover from a chaotic state to a stable state completely controllable, meeting the requirements of industrial applications for real-time performance and accuracy. Furthermore, the performance of the controller for permanent magnet synchronous motors provided in this application embodiment is not sensitive to changes in the initial state and parameters of the system, has strong robustness, and can adapt to uncertainties such as parameter drift and load disturbances during motor operation. In addition, the controller design method for permanent magnet synchronous motors provided in this application embodiment can solve the time delay problem through the historical state error accumulation term, avoiding control lag and oscillation caused by delay.

[0034] like Figure 2 As shown, Figure 2 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; regarding the above step S110, it may include, but is not limited to, steps S210 and S220.

[0035] Step S210: Establish the state equation of the permanent magnet synchronous motor, and set time-varying delay terms to characterize signal transmission delay or system response delay in the state equation to obtain a set of time-varying delay differential equations. Step S220: Adjust the time-varying time-delay differential equation set by the preset chaotic oscillation parameters to obtain a nonlinear mathematical model with time-delay and chaotic characteristics.

[0036] For example, in a permanent magnet synchronous motor (PMSM) system, delays include computational delays in the acquisition of sensor signals from sampling to outputting control quantities, dead time and switching delays in the pulse width modulation inverter, and electromagnetic delays in the motor windings themselves. These delays can cause discrepancies between the model and the actual system, thus affecting the actual control performance of the controller. Therefore, time-varying delay terms can be added to the state equations to mathematically characterize signal transmission delays or system response delays. In some embodiments, establishing the state equations of the PMSM can involve establishing the state equations of the PMSM in a rotating dq coordinate system, describing the changes in the d-axis current, q-axis current, and rotor angular velocity over time in the form of a system of differential equations. The time-varying delay terms can be expressed as functions of the state variables at the delayed time. The introduction of time-varying delays transforms the model into a system of differential equations that includes the current state and the delayed state, enabling a more accurate description of the dynamic behavior of the actual system. By adjusting the time-varying delay differential equations using preset chaotic oscillation parameters, the model can simulate the chaotic phenomena that occur in the motor under specific parameter combinations. Here, chaotic oscillation is the complex dynamic behavior exhibited by a permanent magnet synchronous motor within a specific parameter range. The system state variables appear random but are actually governed by deterministic equations, manifesting as intermittent and violent fluctuations in speed and current, increased electromagnetic noise, and decreased system stability. Therefore, by selecting specific system parameters, such as setting the motor's damping coefficient, flux linkage constant, load torque, etc., within a specific numerical range and coordinating with appropriate time delay parameters, the solution of the differential equation system can exhibit chaotic attractor characteristics.

[0037] In some embodiments, the system phase trajectory diagram can be observed through numerical simulation to determine whether the model is in a chaotic state, so as to obtain a nonlinear mathematical model that has both time delay characteristics and chaotic characteristics. The nonlinear mathematical model includes a delay factor, which can accurately describe the chaotic behavior that the motor may exhibit under specific operating conditions. Thus, the time-varying delay term allows the controller design to consider the delay effect and avoid the control performance degradation or system instability caused by ignoring the delay. The setting of the chaotic parameter allows the controller to be specifically designed for chaotic states, thereby effectively suppressing chaotic oscillations and improving the operating stability of the system.

[0038] like Figure 3 As shown, Figure 3 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; the above step S120 may include, but is not limited to, steps S310, S320 and S330.

[0039] Step S310: Determine the value range of any state variable of the permanent magnet synchronous motor, divide the value range into multiple fuzzy sets, and set corresponding fuzzy rules for each fuzzy set; Step S320: Based on the dynamic parameters under each fuzzy rule, obtain the corresponding linear state-space model; Step S330: The outputs of each linear state-space model are weighted and combined using a preset membership function to obtain a global fuzzy system model.

[0040] It is understandable that the preset fuzzy rules can be TS fuzzy rules. Based on the TS fuzzy rules, the nonlinear mathematical model is linearized to obtain a global fuzzy system model. That is, by fuzzy partitioning and weighted combination, the nonlinear system with time delay is transformed into a combination of multiple local linear subsystems, thereby significantly reducing the complexity of controller design while maintaining high model accuracy.

[0041] For example, TS fuzzy rules are a knowledge-based nonlinear system modeling method that can divide the workspace of the entire system into several fuzzy regions. In each region, a simple linear model is used to approximate the original nonlinear system. Then, the local linear models are combined through membership functions to form a global model. For example, firstly, a certain state variable in the permanent magnet synchronous motor system is determined as the basis for fuzzy partitioning, that is, the premise variable. A state variable that can reflect the nonlinear characteristics of the system can be selected, such as d-axis current, q-axis current, or rotor angular velocity. In one embodiment, d-axis current can be selected as the premise variable and its value range can be determined, which can be set according to the actual operating range of the motor. Then, the value range is divided into multiple fuzzy sets, each fuzzy set corresponding to a fuzzy label. For example, it can be divided into two fuzzy sets M1 and M2, representing two fuzzy states: smaller current and larger current, respectively. For each fuzzy set, a corresponding fuzzy rule is set, which can be expressed in the form of IF-THEN. Rule 1 is that if the premise variable belongs to fuzzy set M1, the system dynamics are approximated as a linear model A1. Rule 2 is that if the premise variable belongs to fuzzy set M2, the system dynamics are approximated as a linear model A2. The linear state space model corresponding to each fuzzy rule is obtained by linearizing the original nonlinear equation in the local region corresponding to the rule. That is, at a typical operating point in the region, the original nonlinear function is expanded by Taylor, and the first-order term is retained to obtain the linearized system matrix.

[0042] After obtaining the local linear models, membership functions can be designed to quantify the degree to which the current system state belongs to each fuzzy set. The membership function can be a continuous function between 0 and 1, including triangular, Gaussian, or trapezoidal functions. In some embodiments, a linear membership function can be used. Subsequently, the output of the global fuzzy system model is equal to the weighted sum of the outputs of each local linear model, with the weights being the membership values ​​of the corresponding rules. This ensures a smooth transition between different fuzzy regions and avoids model abrupt changes caused by region switching. Based on this, through TS fuzzy linearization, the originally complex system of nonlinear differential equations with time delays is transformed into a weighted combination of multiple linear subsystems. This transforms the originally difficult nonlinear controller design problem into a relatively simple linear system controller design problem, greatly reducing the computational complexity and mathematical difficulty of controller design. This allows control methods based on linear system theory to be applied to nonlinear systems. Since the TS fuzzy model can approximate the original nonlinear system with arbitrary precision, the controller designed based on the TS fuzzy model can still maintain good control performance in practical applications. Furthermore, the model retains the structural information of the time delay term, enabling subsequent sliding surface design and controller design to specifically compensate for the effects of time delays, thereby achieving effective control of chaotic systems with time delays.

[0043] like Figure 4 As shown, Figure 4 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; regarding the above step S130, it may include, but is not limited to, steps S410 and S420.

[0044] Step S410: Based on the global fuzzy system model, obtain the current state error term, and obtain the historical state error accumulation term by performing nonlinear weighted accumulation on the historical state errors; Step S420: Generate the sliding surface using the current state error and the historical state error accumulation term.

[0045] For example, based on a global fuzzy system model, the current state error term is obtained, which represents the deviation between the actual operating state of the motor and the desired equilibrium point at each moment. The current state error term characterizes the degree to which the system deviates from the ideal trajectory at any instant. However, for a chaotic permanent magnet synchronous motor system with time-varying delays, relying solely on the current state error cannot effectively compensate for the effects of the delay, because the current control action requires a delay before it has a real impact on the system state, and the current error already includes the results of past control actions. Therefore, a historical state error accumulation term is set in the sliding surface. This historical state error accumulation term can be obtained by nonlinearly weighting and accumulating the historical state errors. Here, nonlinear weighted accumulation refers to assigning different weights to the state errors over a past period according to a certain nonlinear function and performing integration or summation operations, so that earlier errors contribute less and more recent errors contribute more, or different weighting coefficients are used according to the magnitude of the error.

[0046] The sliding surface equation, obtained by adding the current state error to the accumulated historical state error, defines a manifold of the system state in phase space. When the system state lies on the sliding surface, the motion characteristics are determined by the sliding surface itself, automatically compensating for time delay effects and ensuring stable convergence of the system along the desired trajectory. Understandably, the nonlinear weighting mechanism enables the sliding surface to have an adaptive convergence speed within different error ranges, ensuring rapid approach when far from the equilibrium point while avoiding overshoot or slow convergence when approaching the equilibrium point.

[0047] In another embodiment of this application, the controller design method for a permanent magnet synchronous motor includes an equivalent control module and a switching control module. The equivalent control module is used to cancel the current dynamic parameters of the permanent magnet synchronous motor so that the state parameters of the permanent magnet synchronous motor approach the sliding surface; the switching control module includes a time-varying gain term associated with a preset convergence time. The time-varying gain term is used to monotonically increase during the control process as the time approaches the preset convergence time so that the state parameters of the permanent magnet synchronous motor reach the sliding surface within the preset convergence time.

[0048] For example, the sliding mode controller is designed based on a pre-constructed sliding surface to generate a suitable control voltage signal applied to the permanent magnet synchronous motor (PMSM), forcing the system's state variables onto the sliding surface and allowing them to slide along the surface to the equilibrium point. Based on this, the controller can consist of two parts: an equivalent control module and a switching control module. The equivalent control module is used to cancel the current dynamic parameters of the PMSM system, allowing the system state to approach the sliding surface. Here, equivalent control refers to the control required to maintain the state's movement on the sliding surface when, ideally, the system state is already on the sliding surface. Specifically, the equivalent control module needs to calculate the system's current state, time-delay state, and known nonlinear terms based on a global fuzzy system model and design a control law to cancel them out, allowing the system to naturally approach the sliding surface without disturbance. The equivalent control module can include state feedback terms and time-delay compensation terms; for example, it can be designed as a linear combination related to the current state and the delayed state to cancel out the effects of the system matrix and the time-delay matrix.

[0049] The switching control module generates a discontinuous control action to overcome system uncertainties, external disturbances, and the effects of initial state deviation from the sliding surface, forcing the system state to reach the sliding surface within a finite time. The switching control module incorporates a time-varying gain term associated with a preset convergence time. This time-varying gain term constructs a gain function that monotonically increases with time and approaches infinity at a preset time, ensuring that the system state, regardless of its initial deviation, is driven to the sliding surface before the preset time point. Specifically, when the system state is far from the sliding surface, the switching control module generates a large control action, rapidly driving the state towards the sliding surface; when the time approaches the preset cutoff time and the state has not yet reached the sliding surface, the gain increases sharply, generating a very strong control force, forcing the state to precisely reach the sliding surface before the cutoff time.

[0050] The outputs of the equivalent control module and the switching control module are added together to obtain the final control quantity applied to the motor. In this way, the equivalent control module reduces the control burden on the switching control module, allowing the switching gain to be designed to be relatively small, thereby effectively suppressing chattering, a common phenomenon in traditional sliding mode control. Because the time-varying gain term is combined with the sliding surface, even with large initial deviations or parameter perturbations, the controller can ensure that the sliding surface is reached within a preset time, enhancing robustness and adaptability.

[0051] In another embodiment of this application, the controller design method for a permanent magnet synchronous motor is provided, wherein the time-varying gain term is obtained by the difference between the preset convergence time and the current time; the time-varying gain term includes a nonlinear term related to the sliding surface, which is used to adjust the control intensity at different stages.

[0052] For example, the time-varying gain term is determined by the difference between the preset convergence time and the current time, and can be expressed as the reciprocal of the difference between the preset convergence time and the current time, or a power function of that reciprocal. For instance, suppose the convergence time preset by the engineer according to application requirements is T_c, and the current running time is t. Then the basic framework of the time-varying gain term is T_c / (T_c - t) or its power function form. As time t gradually increases from 0 and approaches T_c, the denominator (T_c - t) gradually decreases, making the entire gain term monotonically increasing. When t approaches T_c infinitely, the gain term tends to infinity. In the initial stage of the control process, the gain value is relatively small, and the control action drives the system state to move towards the sliding surface in a relatively gentle manner. As time goes by, the gain gradually increases, and the control force is continuously strengthened. When the preset cutoff time is approached and the system state has not yet fully reached the sliding surface, the gain increases sharply to a theoretically infinite level, generating an extremely strong control action, forcibly pushing the system state onto the sliding surface, ensuring that no matter how far the initial state deviates from the sliding surface, the system will inevitably reach the sliding surface at time t=T_c, thus achieving complete decoupling between the arrival time and the initial state.

[0053] Furthermore, the time-varying gain term also includes a nonlinear term related to the sliding surface, used to adjust the control intensity at different stages. Here, the nonlinear term related to the sliding surface refers to the gain term incorporating a nonlinear transformation of the sliding surface function. This nonlinear adjustment mechanism ensures that the controller maintains appropriate control intensity at different stages, avoiding slow convergence due to insufficient control action in the initial stage, and preventing the steady-state error from being difficult to eliminate due to excessively rapid decay of control action near the sliding surface. In practical implementation, the time-varying gain term is multiplied by the sign function of the sliding surface to obtain the main output of the switching control module, and the output of the equivalent control module is added to it to form the complete control law.

[0054] like Figure 5 As shown, Figure 5 This is a flowchart of a controller design method for a permanent magnet synchronous motor provided in another embodiment of this application; the above method may also include, but is not limited to, step S150.

[0055] Step S150: Verify the stability of the sliding mode controller using preset stability verification rules.

[0056] Understandably, in the design of a control system, it is necessary to mathematically prove that the controller can enable the system to achieve the expected control objective, that is, the system state can converge to the equilibrium point and remain stable within a preset time. In one embodiment, the stability of the sliding mode controller is verified by a preset stability verification rule. The preset stability verification rule can adopt Lyapunov stability theory, by constructing a positive definite energy function and then analyzing the rate of change of this function with time. If the energy function always decreases and eventually tends to zero, the system is stable.

[0057] For example, the controller design method for a permanent magnet synchronous motor provided in this application first establishes a mathematical model of the permanent magnet synchronous motor containing time delay and chaotic characteristics: Consider the following permanent magnet synchronous motor system model:

[0058] in, It is a constant. It is time-varying and time-delayed, and when From time to time Note that under given conditions, the system may exhibit chaotic behavior. Take the system parameters. And the initial value is (in The phase trajectory diagram of this system is as follows: Figure 6 As shown, Figure 6 This is a phase trajectory diagram of a permanent magnet synchronous motor system provided in another embodiment of this application, wherein the initial conditions are: .

[0059] Establishing a fuzzy system model based on TS fuzzy rules: First, assume ,like Belonging to different fuzzy sets Using the TS fuzzy method, the permanent magnet synchronous motor system can be represented as: Rule 1: If belong ,but , Rule 2: If belong ,but , in, , , For controller, and It is the gain matrix to be designed.

[0060]

[0061]

[0062] And the membership function is:

[0063] Therefore, we can obtain:

[0064] in, .

[0065] Design of sliding surfaces and sliding control: Before proceeding with the following steps, let's first provide some definitions and lemmas: Definition 1: If there exists a pre-given time... , making

[0066] This is referred to as the controller in the design. Under the influence of time delay and chaotic characteristics, permanent magnet synchronous motors can achieve stable control at a specified time.

[0067] Lemma 1: For any real number ,as well as The following two inequalities hold:

[0068] Based on this, firstly, the following is defined for the sliding face:

[0069] in

[0070] in, , It is a symbolic function.

[0071] Therefore, for Differentiation yields:

[0072] Assuming at a specified time If the inner reaches the sliding surface, then for all have Furthermore, it is assumed that the designed sliding surface will be within a specified time. The system reaches equilibrium within the system, from which we can conclude:

[0073] To ensure that the permanent magnet synchronous motor system reaches a stable state within a specified time, the following specified-time sliding mode controller is designed:

[0074] in, The controller parameters satisfy .

[0075] Achieving stability control of permanent magnet synchronous motors with time delay and chaotic characteristics: First, verify the reachability of the sliding surface of the permanent magnet synchronous motor system under the action of the designed controller by selecting the following Lyapunov function:

[0076] Taking the derivative of this Lyapunov function, we get:

[0077] Substituting the designed controller into the differentiated Lyapunov function, we can obtain:

[0078] Based on Lemma 1, we can obtain:

[0079] The time for the permanent magnet synchronous motor system to reach the sliding surface can be obtained from the above formula. :

[0080] Next, when the permanent magnet synchronous motor system reaches the designed sliding surface, the system's state variables will be further updated at a specified time. It converges to the equilibrium point. To verify this, the following Lyapunov function is designed:

[0081] Taking the derivative of this Lyapunov function, we get:

[0082] Based on Lemma 1, we can obtain:

[0083] Finally, the time for the state variables of the permanent magnet synchronous motor system to converge to the equilibrium point can be obtained. :

[0084] Therefore, the state variables of a permanent magnet synchronous motor system with time delay and chaotic characteristics first appear at a specified time. The system approaches and reaches the designed sliding surface; after reaching the sliding surface, the system's state variables will be determined at a subsequent specified time. It converges to the equilibrium point, therefore the total specified time is [time]. satisfy In other words, at a specified time The system achieves stability control of permanent magnet synchronous motors with time delay and chaotic characteristics.

[0085] In one embodiment, the effectiveness of the controller design method for the permanent magnet synchronous motor provided in this application can be verified by simulation. The mathematical model of the permanent magnet synchronous motor system with time delay and chaotic characteristics is shown below:

[0086] Pick The initial conditions for a permanent magnet synchronous motor system with time delay and chaotic characteristics are selected as follows: (in The trajectory of the system's state variables without control is as follows: Figure 7 As shown, Figure 7 This is a system state trajectory diagram of a simulated permanent magnet synchronous motor system without control, provided in another embodiment of this application, which shows that the state is unstable.

[0087] Then, the system is transformed into the following linear system using the designed TS fuzzy method: Rule 1: If belong ,but , Rule 2: If belong ,but , The parameters are selected as follows:

[0088]

[0089] Pick And the membership function is:

[0090] Select parameters Select the total specified time ,in Based on the results verified in the above steps, the state variables of a permanent magnet synchronous motor system with time delay and chaotic characteristics will be determined at a specified time. The system approaches and reaches the designed sliding surface; after reaching the sliding surface, the system state will be updated at a specified time. When the system converges to an equilibrium point, stability control of the permanent magnet synchronous motor system, which exhibits time delay and chaotic characteristics, is achieved. At that time, the system state The trajectory is as follows Figure 8 As shown, Figure 8 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application, wherein, In addition, select the total specified time. At that time, among them The trajectory of the system state is as follows Figure 9 As shown, the system state trajectory converges to zero within a specified time of 0.1s; Figure 9 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application, wherein, The system state trajectory diagram at that time.

[0091] To verify that the specified time is independent of the system's initial value, the system's initial value is magnified by 100 times. And provide the corresponding simulation results, such as Figure 10 and Figure 11 As shown, Figure 10 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application, wherein, ; Figure 11 This is a state trajectory diagram of a simulated permanent magnet synchronous motor system provided in another embodiment of this application, wherein, Therefore, it can be seen that the system state trajectory under different initial values ​​can still converge to zero within a specified time, which verifies the superiority of the preset time control method.

[0092] Based on the controller design method of the permanent magnet synchronous motor in the above embodiments, the following presents various embodiments of the operation control device, electronic device, computer-readable storage medium and computer program product of this application.

[0093] like Figure 12 As shown, Figure 12 This is a schematic diagram of an operation control device for executing a controller design method for a permanent magnet synchronous motor, according to an embodiment of this application. The operation control device 1200 implemented in this application includes: a processor 1220, a memory 1210, and a computer program stored in the memory 1210 and executable on the processor 1220, wherein... Figure 12 The example uses a processor 1220 and a memory 1210.

[0094] Processor 1220 and memory 1210 can be connected via a bus or other means. Figure 12 Taking the example of a connection between China and Israel via a bus.

[0095] Memory 1210, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory 1210 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 1210 may optionally include remotely located memories 1210 relative to processor 1220, which can be connected to the operation control device 1200 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0096] Those skilled in the art will understand that Figure 12 The device structure shown does not constitute a limitation on the operation control device 1200, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0097] exist Figure 12 In the operation control device 1200 shown, the processor 1220 can be used to call the control program stored in the memory 1210, thereby implementing the controller design method for the permanent magnet synchronous motor described above. Specifically, the non-transient software program and instructions required to implement the controller design method for the permanent magnet synchronous motor of the above embodiment are stored in the memory 1210. When executed by the processor 1220, the controller design method for the permanent magnet synchronous motor of the above embodiment is executed.

[0098] It is worth noting that, since the operation control device 1200 of this application embodiment can execute the controller design method of the permanent magnet synchronous motor of any of the above embodiments, the specific implementation method and technical effect of the operation control device 1200 of this application embodiment can refer to the specific implementation method and technical effect of the controller design method of the permanent magnet synchronous motor of any of the above embodiments.

[0099] Furthermore, one embodiment of this application also provides an electronic device that includes the operation control device described in the above embodiment.

[0100] It is worth noting that, since the electronic device of this application embodiment includes the operation control device of the above embodiment, and the operation control device of the above embodiment can execute the controller design method of the permanent magnet synchronous motor of any of the above embodiments, the specific implementation method and technical effect of the electronic device of this application embodiment can refer to the specific implementation method and technical effect of the controller design method of the permanent magnet synchronous motor of any of the above embodiments.

[0101] Furthermore, one embodiment of this application provides a computer-readable storage medium storing computer-executable instructions for executing the aforementioned controller design method for a permanent magnet synchronous motor. Exemplarily, the above-described method is executed... Figures 1 to 5 The methods and steps in the text.

[0102] It is worth noting that, since the computer-readable storage medium of this application embodiment can execute the controller design method of the permanent magnet synchronous motor of any of the above embodiments, the specific implementation method and technical effect of the computer-readable storage medium of this application embodiment can refer to the specific implementation method and technical effect of the controller design method of the permanent magnet synchronous motor of any of the above embodiments.

[0103] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which may include computer storage media or non-transitory media and communication media or transient media. As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc DVD or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0104] In the several embodiments provided in this application, it should be understood that the disclosed systems, instruments, and methods can be implemented in other ways. For example, the instrument embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between instruments or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0105] It should also be understood that the various implementation methods provided in this application can be combined arbitrarily to achieve different technical effects.

[0106] The embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of this application.

Claims

1. A controller design method for a permanent magnet synchronous motor, characterized in that, include: A nonlinear mathematical model of the permanent magnet synchronous motor is established, and the nonlinear mathematical model is used to determine the parameter conditions for chaotic oscillation. The nonlinear mathematical model is linearized based on preset fuzzy rules to obtain a global fuzzy system model. The global fuzzy system model generates a sliding surface that includes the current state error and the cumulative term of the historical state error. The sliding surface is used to define the convergence path. A sliding mode controller is generated based on the sliding surface. The sliding mode controller includes a time-varying gain term associated with a preset convergence time, so that the system state variables converge to the equilibrium point within the preset convergence time.

2. The controller design method for a permanent magnet synchronous motor according to claim 1, characterized in that, The establishment of the nonlinear mathematical model of the permanent magnet synchronous motor includes: Establish the state equation of the permanent magnet synchronous motor, and set a time-varying delay term to characterize the signal transmission delay or system response delay in the state equation to obtain a set of time-varying delay differential equations. By adjusting the time-varying time-delay differential equations with preset chaotic oscillation parameters, a nonlinear mathematical model with time-delay and chaotic characteristics is obtained.

3. The controller design method for a permanent magnet synchronous motor according to claim 1, characterized in that, The linearization process of the nonlinear mathematical model based on preset fuzzy rules to obtain a global fuzzy system model includes: Determine the value range of any state variable of the permanent magnet synchronous motor, divide the value range into multiple fuzzy sets, and set corresponding fuzzy rules for each fuzzy set; Based on the dynamic parameters under each of the fuzzy rules, the corresponding linear state-space model is obtained; By weighting and combining the outputs of each linear state-space model using a preset membership function, a global fuzzy system model is obtained.

4. The controller design method for a permanent magnet synchronous motor according to claim 1, characterized in that, The step of generating a sliding surface, including the current state error and the cumulative term of historical state error, through the global fuzzy system model includes: Based on the global fuzzy system model, the current state error term is obtained, and the historical state error accumulation term is obtained by nonlinearly weighting and accumulating the historical state errors. A sliding surface is generated using the current state error and the accumulated historical state error.

5. The controller design method for a permanent magnet synchronous motor according to claim 1, characterized in that, The sliding mode controller includes an equivalent control module and a switching control module; The equivalent control module is used to offset the current dynamic parameters of the permanent magnet synchronous motor so that the state parameters of the permanent magnet synchronous motor approach the sliding surface; the switching control module includes a time-varying gain term associated with a preset convergence time, which is used to monotonically increase during the control process as the time approaches the preset convergence time so that the state parameters of the permanent magnet synchronous motor reach the sliding surface within the preset convergence time.

6. The controller design method for a permanent magnet synchronous motor according to claim 5, characterized in that, The time-varying gain term is obtained by the difference between the preset convergence time and the current time; the time-varying gain term includes a nonlinear term related to the sliding surface, which is used to adjust the control intensity at different stages.

7. The controller design method for a permanent magnet synchronous motor according to claim 1, characterized in that, Also includes: The stability of the sliding mode controller is verified using preset stability verification rules.

8. An operation control device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the controller design method for a permanent magnet synchronous motor as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, Includes the operation control device as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the controller design method for a permanent magnet synchronous motor as described in any one of claims 1 to 7.

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