A dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motor

Abstract

The application discloses a kind of permanent magnet synchronous motor dynamic event trigger deadbeat prediction speed control method, comprising: step S1, step S1, PMSM mathematical modeling motion equation, calculate the speed tracking error of next time;Step S2, calculate the ideal control law of deadbeat prediction speed control, disturbance estimation compensation is used, to generate actual control law;Step S3, introduce dynamic event trigger mechanism, and update actual control law according to dynamic event trigger condition;Step S4, construct composite Lyapunov function, respectively, stability analysis is carried out to trigger time and non-trigger interval;Step S5, after dynamic event trigger judgment, output final control law is applied to current loop to generate d, q axis reference voltage, after d, q axis reference voltage is converted into inverter driving signal by SVPWM module, it is applied to permanent magnet synchronous motor.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet synchronous motor control technology, and in particular to a dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) possess advantages such as high power density, high efficiency, and good speed regulation performance, and have been widely used in electric vehicles, industrial servos, robots, and multi-motor cooperative drives. As the requirements for dynamic response, steady-state accuracy, and real-time performance in control systems continue to increase, traditional proportional-integral (PI) control methods struggle to simultaneously balance response speed, anti-interference capability, and constraint handling ability under complex operating conditions. Therefore, model predictive control has gradually become an important research direction for high-performance control of PMSMs.

[0003] Continuous control set model predictive control (MCC) can predict future states using discrete motor models and obtain control laws through value function optimization. Compared with traditional control methods, this method can handle physical constraints such as current and voltage more naturally and is easier to incorporate multi-objective performance indicators such as speed tracking error, control increment, and synchronization error. However, traditional MCC typically requires recalculating the control input in each sampling period. When the sampling period is short, the prediction step size is large, or the controller is running on an embedded platform, frequent calculations of the optimal control input increase computational burden and may also lead to unnecessary control updates when the error is small.

[0004] The basic idea of ​​event-triggered control is to determine whether the controller updates based on changes in the system state, rather than simply updating according to a fixed period. If the system error is within the allowable range, the control law at the previous trigger time is maintained; if the error exceeds a set threshold, the controller is triggered to recalculate the control input. Compared to static threshold event triggering, dynamic event triggering mechanisms introduce auxiliary variables, allowing the trigger threshold to adjust with changes in the system state, thereby achieving a better balance between control performance and computational resources.

[0005] Therefore, a predictive speed control method for permanent magnet synchronous motors needs to be proposed to reduce unnecessary control updates and lower the online computation load of the controller while maintaining speed tracking performance and closed-loop stability. Summary of the Invention

[0006] The purpose of this invention is to provide a dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors, which solves the problem of high online computational burden caused by repeated calculation of the control law in each sampling period in traditional predictive speed control, and improves the stability of the control system while ensuring speed tracking performance.

[0007] The technical solution adopted to achieve the purpose of this invention is: A dynamic event-triggered deadbeat predictive speed control method for a permanent magnet synchronous motor includes the following steps: Step S1: Establish the mechanical motion equations of the permanent magnet synchronous motor (PMSM) and obtain a discrete model of the PMSM's mechanical angular velocity through discretization, thus constructing the speed tracking error. ,right The velocity tracking error at the next moment is derived and then organized into the standard velocity tracking error system form. Step S2: Calculate the ideal control law for deadbeat predictive speed control based on the standard speed tracking error system form obtained in Step S1, using the disturbance estimate. Replace the real disturbance in the ideal control law Thus, the actual control law for deadbeat predictive speed control is obtained; Step S3: For the actual control law in step S2, set the dynamic event triggering condition as follows. ,in, For dynamically triggered variables, For the trigger parameters, if the dynamic event triggering conditions are met, the new actual control law is recalculated and output; otherwise, the actual control law at the previous triggering moment remains unchanged, and the dynamic trigger variable is set. The update law is , The attenuation coefficient is, and , Historical error weighting coefficients, It is a non-negative compensation term, and , For the first The square of the velocity tracking error at the next trigger moment; Step S4, based on and Construct a composite Lyapunov function and perform stability analysis on both the triggering time and the non-triggering interval; Step S5: Under stable system conditions, apply the actual control law of the deadbeat prediction speed after the dynamic event trigger judgment in step S3. As the input to the current loop, the d-axis and q-axis reference voltages are generated after PI calculation in the current loop. , ,Will , After being converted into an inverter drive signal by the SVPWM module, it is applied to the permanent magnet synchronous motor.

[0008] In the above technical solution, the prediction expression for the velocity tracking error at the next moment in step S1 is: ; In the formula, for Velocity tracking error at sampling time for Velocity tracking error at sampling time For the moment of inertia of the motor, The coefficient of viscous friction, for Load torque at the sampling time The sampling period is This is the torque coefficient of the permanent magnet synchronous motor. for The q-axis component of the stator current at the sampling time. Sampling time, Given a mechanical angular velocity; The prediction expression for the next-moment velocity tracking error in the standard velocity tracking error system form is: ; In the formula, Let be the speed tracking error coefficient, where , Let be the control law coefficient, where , for Control law at sampling time, This is the system's actual disturbance term, which includes load torque and reference input related terms. .

[0009] In the above technical solution, in step S2, by ensuring that the speed tracking error at the next moment is zero in the form of a standard speed tracking error system, the ideal control law for deadbeat predictive speed control is obtained. The calculation formula for the ideal control law is as follows: ; In the formula, For ideal control laws; Using disturbance estimates Replace the real disturbance in the ideal control law The actual control law is obtained, and the formula for calculating the actual control law is: ; In the formula, for The disturbance estimate at the sampling time.

[0010] In the above technical solution, the calculation formula for the actual control law in step S3 is as follows: ; In the formula, The control law is calculated by the predictive controller at the current moment. For the first Control law at the next trigger moment For the first Next trigger moment For the trigger parameters, where, , This is a dynamically triggered variable.

[0011] In the above technical solution, the calculation formula for the composite Lyapunov function in step S4 is as follows: ; In the formula, for k Composite Lyapunov functions at sampling time, These are the weighting coefficients, and .

[0012] In the above technical solution, in step S4, within the non-trigger interval, the composite Lyapunov function satisfies the linear recursion inequality. ,in, The recursive contraction coefficient is, and , The nonnegative constant is determined by the perturbation estimation bias, the bounded perturbation, and the nonnegative compensation term. Iterating through this inequality, we can see that... It will not grow indefinitely with the number of sampling steps; at this point, the difference of the composite Lyapunov function is compressed to a value derived from... Within the defined scope, and because The speed tracking error remains bounded within the non-triggering range, and the system is stable. At the triggering time, the composite Lyapunov function satisfies the compression inequality. ,in The composite Lyapunov function value at the time preceding the trigger. The composite Lyapunov function value at the time following the trigger. Let be the contraction coefficient at the trigger time, and , For the moment before triggering, After each trigger, the system contracts once, thus suppressing the growth of velocity tracking error, until the velocity tracking error eventually satisfies... This means that the speed tracking error remains bounded at the trigger moment, and the system is stable.

[0013] A second aspect of the present invention is an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the dynamic event-triggered deadbeat predictive speed control method for a permanent magnet synchronous motor.

[0014] A third aspect of the present invention is a computer-readable storage medium, characterized in that it stores computer-executable instructions, which, when executed, are used to implement the dynamic event-triggered deadbeat predictive speed control method for a permanent magnet synchronous motor.

[0015] In a fourth aspect, the present invention provides a computer program product comprising computer-executable instructions which, when executed, implement the dynamic event-triggered deadbeat predictive speed control method for a permanent magnet synchronous motor.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention introduces a dynamic event triggering mechanism on the basis of the existing predictive speed control framework for permanent magnet synchronous motors. It determines whether to trigger a control update based on the relationship between the speed tracking error and the dynamic threshold, so that the control law is no longer recalculated in every sampling period, thereby reducing unnecessary online calculations; 2. This invention recalculates the control law when the triggering condition is met, and keeps the control law unchanged at the previous triggering moment when the triggering condition is not met, so that the control update frequency can be adjusted according to the changes in the system operating state; 3. This invention derives a deadbeat predictive speed control law based on the speed tracking error model, which enables the speed tracking error at the next sampling moment to have a rapid suppression trend, which is beneficial to ensuring the speed tracking performance of the permanent magnet synchronous motor; 4. This invention constructs a composite Lyapunov function that includes velocity tracking error and dynamic triggering variables, and performs stability analysis on the triggering time and non-triggering intervals respectively, which can ensure that the closed-loop error system is consistent and eventually bounded. Attached Figure Description

[0017] Figure 1 This is a block diagram of the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors according to the present invention.

[0018] Figure 2 This is a flowchart of the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors according to the present invention. Detailed Implementation

[0019] The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] Example 1 A dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors, referring to... Figure 1 , Figure 2 This includes the following steps: Step S1: Establish the mechanical motion equations of the permanent magnet synchronous motor (PMSM) and obtain the discrete model of the PMSM's mechanical angular velocity through discretization, defining the speed tracking error. Derive the velocity tracking error at the next moment. It was then organized into a standard speed tracking error system form.

[0021] This invention uses a surface-mounted permanent magnet synchronous motor, and the mechanical motion equation of the permanent magnet synchronous motor is expressed as: ; In the formula, For the moment of inertia of the motor, For time, Here is the torque coefficient of the PMSM, and , It is a permanent magnet flux linkage. For extreme logarithms, This refers to the q-axis component of the stator current. For load torque, The coefficient of viscous friction, This refers to the mechanical angular velocity.

[0022] The mechanical motion equations of the permanent magnet synchronous motor are discretized using the forward Euler method, resulting in a discrete model of the PMSM's mechanical angular velocity, expressed as: ; In the formula, for Mechanical angular velocity at the sampling time, The sampling period is Sampling time, for k Mechanical angular velocity at the sampling time, for The q-axis component of the stator current at the sampling time.

[0023] As can be seen from the discrete model of mechanical angular velocity in PMSM, the mechanical angular velocity at the next sampling moment is determined by the current angular velocity, q-axis current and load torque.

[0024] Based on the mechanical angular velocity, the speed tracking error is defined as: ; In the formula, for k Velocity tracking error at sampling time Given a mechanical angular velocity.

[0025] If the given velocity remains constant within adjacent sampling periods, then: ; In the formula, for Velocity tracking error at the sampling time.

[0026] Substituting the discrete model of the PMSM mechanical angular velocity into the velocity tracking error expression, we get: ; In the formula, for k Load torque at the sampling time.

[0027] To facilitate subsequent control law design, the above equation is written in the form of a standard speed tracking error system: ; In the formula, Let be the speed tracking error coefficient, where , Let be the control law coefficient, where , for Control law at sampling time, This is the system's actual disturbance term, which includes load torque and reference input related terms. .

[0028] Step S2: Based on the standard speed tracking error system obtained in step S1, set the speed tracking error to zero at the next moment, i.e. The ideal control law for deadbeat predictive speed control is obtained. Considering the uncertainties in load torque, friction terms, and model parameters during the actual operation of the permanent magnet synchronous motor, the actual disturbance term is... It is difficult to obtain the complete value, so a perturbation estimate is used. Replace the real perturbation term Thus, a practically usable deadbeat predictive speed control law is obtained.

[0029] According to the standard error system form, if we want the velocity tracking error to be zero at the next sampling time, that is... Then we have: ; Therefore, the ideal control law for the zero-beat prediction speed can be obtained as follows: ; In actual PMSM systems, there may be uncertainties in load torque and model parameters, and the actual disturbance term... Since it is difficult to obtain the exact value, the disturbance estimate obtained by the observer is used. Replacing the actual disturbance term, the actual control law for the deadbeat predictive velocity is obtained as follows: ; In the formula, The actual control law for predicting speed without deadbeats. for k The disturbance estimate at the sampling time.

[0030] Substituting the actual control law of the deadbeat prediction speed We can obtain: ; Therefore, when the disturbance estimate is close to the actual disturbance term, the speed tracking error will be effectively suppressed; when the disturbance estimate has an error, the speed tracking error is mainly determined by the disturbance estimate.

[0031] Step S3: For the deadbeat prediction speed control law in step S2, a dynamic event triggering mechanism is introduced, and the dynamic event triggering condition is set as follows: ,in, For dynamically triggered variables, As a trigger parameter, when the dynamic event triggering condition is met, the controller recalculates and outputs a new control law; otherwise, it indicates that the current speed tracking error is within the allowable range, and the system maintains the control law from the previous triggering moment. Furthermore, a dynamic trigger variable is set, and its update law is designed to provide a basis for triggering judgment in the next sampling period.

[0032] Let the first The trigger time is The next trigger time is In the non-triggering zone Within this timeframe, the actual control law for the zero-beat prediction speed remains at the value of the previous trigger moment, i.e.: ; In the formula, For the first Control law at the next trigger moment.

[0033] At the trigger time The controller recalculates the control law based on the current error and disturbance estimates: ; In the formula, The control law is recalculated by the predictive controller at the current moment. For the first Speed ​​tracking error at the moment of triggering For the first s The estimated value of the disturbance at the next trigger time.

[0034] To avoid the problem of fixed threshold event triggering methods failing to balance control performance and triggering frequency under different operating conditions, the following dynamic event triggering conditions are designed: ; In the formula, for k The square of the velocity tracking error at the sampling time, For the trigger parameters, where, , This is a dynamically triggered variable.

[0035] when When the condition is met, the controller triggers and updates the control law; otherwise, the control law retains the value at the previous trigger moment. Therefore, the actual control law for deadbeat predictive velocity is expressed as: ; In the formula, The control law is recalculated by the predictive controller at the current moment. For the first Control law at the next trigger moment.

[0036] At the same time, dynamically trigger variables The update law is designed as follows: ; In the formula, for Dynamic triggering variables at the sampling time, The attenuation coefficient is, and , Historical error weighting coefficients, It is a non-negative compensation term, and , For the first The square of the velocity tracking error at the next trigger moment.

[0037] Dynamic trigger variables The update law triggers memory items through history. With the current error negative feedback term The synergistic effect of these factors enables adaptive adjustment of the event trigger threshold: when the speed tracking error... When the value is large, the negative feedback term dominates the update law, forcing... Reduce, thereby lowering the dynamic threshold. This makes it easier for the system to trigger control updates and accelerates dynamic response; once the speed tracking error converges to a smaller range... The inhibitory effect weakens, and the historical term and the compensation term... Jointly maintain At a higher level, the trigger threshold is raised to shield against minor disturbances and measurement noise, effectively reducing unnecessary control updates.

[0038] Step S4, based on and A composite Lyapunov function is constructed, and stability analysis is performed on both the triggered time and the non-triggered interval. At the triggered time, the controller updates the control law, causing the system energy to contract. In the non-triggered interval, although the control law remains unchanged, it can be proven through dynamic threshold constraints and Lyapunov difference analysis that the system error will not diverge. Thus, the closed-loop error system is uniformly and eventually bounded.

[0039] Furthermore, the composite Lyapunov function is expressed as: ; In the formula, for k Composite Lyapunov functions at sampling time, These are the weighting coefficients, and .

[0040] Among them, due to dynamic trigger variables Used to define event triggering thresholds Its value must always satisfy Otherwise, the triggering condition will degenerate (threshold). When it becomes negative, the condition is... If the condition is always true (greater than or equal to a negative number), the system will trigger every cycle, completely negating the computational advantage of event-triggered variables. To ensure this, a non-negative compensation term is introduced into the update law of the dynamic trigger variable. And select initial values , making For all Hengcheng and Therefore, composite Lyapunov functions satisfy And only if Sometimes, and Therefore, composite Lyapunov functions can be used as an effective tool for determining the stability of closed-loop systems.

[0041] To quantitatively characterize the energy variation trend of the composite Lyapunov function between adjacent sampling times and thus determine the stability of the closed-loop system, the difference of the composite Lyapunov function is calculated. The formula for calculating the difference is: ; In the formula, For the difference of composite Lyapunov functions, for Composite Lyapunov functions at time t; According to the formula Let the tracking error energy difference be... Dynamically triggered variable differencing ,but ; During the non-triggered interval, the control law remains at the value of the previous trigger moment, i.e. The deadbeat control law at the trigger moment. Substituting into the standard discrete error dynamic equation By refining the data, we can obtain the recursive relationship for the velocity tracking error during non-triggering periods: ; In the formula, For the first Speed ​​tracking error at the moment of triggering For the first The estimated value of the disturbance at the next trigger time.

[0042] Let the error offset Perturbation estimation bias The recursive relationship of speed tracking error can be expressed as: ; In the formula, Let be the velocity tracking error coefficient. This recursive relationship shows that, during non-triggered periods, the evolution of the velocity tracking error is only affected by the open-loop dynamics and disturbance estimation bias.

[0043] Assume that the error estimation bias is bounded, i.e., there exists a normal constant. Make: ; From the error recursion relationship and We can obtain: ; Further expansion yields: ; And because ,Right now Therefore: ; Calculate the upper bound of the energy difference for tracking error. : ; On the other hand, the difference of the dynamic trigger variables is further calculated based on the dynamic trigger variable update law: ; Substituting the upper bound of the tracking error energy difference and the difference of the dynamic trigger variable into the difference of the composite Lyapunov function, and simplifying, we get: ; In the formula, 、 、 The coefficient is obtained by combining like terms.

[0044] By about and It consists of quadratic terms, dynamic variable terms, and disturbance-related terms. For To simplify, specifically: Since the conditions for triggering a dynamic event are not met at this time, that is: ; And because Therefore, dynamically triggered variables satisfy: ; And because ,therefore .Will Substituting into the difference of the composite Lyapunov function Item, can be further Sorted as: ; In the formula, , , The coefficients obtained after substituting them into the dynamic threshold constraint are, and , , .

[0045] To ensure that the quadratic term in the above equation is negative definite, appropriate parameters can be selected. , and To make it satisfy the negative definite criterion of quadratic form and Then there exist positive constants. , so that: ; in, therefore, Represented as: ; For the disturbance cross term Using Young's inequality, we have: ; Substitute it And select parameters to make have to: ; And because ,therefore Able to By establishing a lower bound constraint, we can obtain: ; And there are positive numbers. θ , so that: ; Let non-negative compensation term be defined. Bounded, that is And order: ; In the formula, The term is a nonnegative constant determined by the perturbation estimation bias, the bounded perturbation, and the nonnegative compensation term. Non-negative compensation term The maximum value.

[0046] but It can be written as: ; In the formula, for The composite Lyapunov function value at the sampling time. It is a positive number.

[0047] Using non-triggering conditions and , can be obtained ; therefore ; Substitute it into the above formula After sorting and organizing, we get: ; In the formula, This is the recursive shrinkage coefficient, and by appropriately selecting parameters, it can be made... .

[0048] The shrinkage relationship of the non-triggering interval indicates that, within the non-triggering interval, although the control law remains unchanged at the value of the previous triggering moment, the composite Lyapunov function is still constrained by the linear recursion inequality and will not increase indefinitely with the sampling time. Therefore, the system error will not diverge within the non-triggering interval, and the system is stable.

[0049] At the triggering time, when the trigger occurs At that time, the dynamic event triggering condition is met, that is: ; At this point, the controller recalculates the control law based on the current speed tracking error and disturbance estimate. According to the standard error system of the actual control law, the speed tracking error at the next moment after triggering is mainly determined by the disturbance estimation deviation. When the disturbance estimation deviation is bounded, the speed tracking error after triggering is also bounded. Simultaneously, the dynamic trigger variable is readjusted according to its update law, ensuring the dynamic threshold continues to participate in the triggering judgment of the next sampling period. Therefore, by selecting appropriate dynamic parameters, at the triggering moment, the composite Lyapunov function satisfies the contraction relationship at the triggering moment, expressed as: ; In the formula, The composite Lyapunov function value at the time preceding the trigger. The composite Lyapunov function value at the time following the trigger. Let be the contraction coefficient at the trigger time, and , For the moment before triggering, This is the time immediately following the trigger. This indicates that each trigger causes a contraction in the system's composite energy, thereby suppressing the growth of velocity tracking error and stabilizing the system.

[0050] Finally, the conclusion that the system is stable is proved by combining the linear recursive relationship in the non-triggering interval and the contraction relationship at the triggering time. Specifically: 1) In the non-trigger interval, let the first... After the first trigger until the [number]th The non-triggering interval before the next trigger, if the interval contains For each sampling period, the non-trigger interval inequality will be applied. From the start of the non-triggering interval If the iteration begins at the first sampling point after the trigger ends, then: ; In the formula, For the first The composite Lyapunov function value at the moment before the trigger.

[0051] because ,when hour, ,therefore: ; This recursion shows that even if the controller is not updated, the composite energy does not increase indefinitely with the number of sampling steps, but is compressed to a value determined by... Within the defined scope. And because... The speed tracking error remains bounded within the non-triggering range, preventing divergence and loss of control due to control hold, thus ensuring system stability.

[0052] 2) At the triggering moment, substitute the contraction formula for the triggering moment into... ,have to: ; because ,have and ,therefore: ; make , but: ; In the formula, For the first The composite Lyapunov function value at the moment before the trigger. For the composite Lyapunov function of the time step preceding the trigger. This is a constant term.

[0053] right Perform recursion: from Recursion to ,have: ; because ,when hour, ,therefore: ; Right now: ; because ,but: ; Therefore, speed tracking error It eventually converges to the parameter , , Within the determined bounds, the system satisfies the condition of being uniformly eventually bounded, and the system is stable.

[0054] Therefore, under the conditions of bounded disturbance and reasonable parameter selection, the proposed dynamic event-triggered predictive velocity control strategy can ensure that the closed-loop error system is consistent and eventually bounded, and the system state will not diverge over time. That is, the event-triggered mechanism can still maintain the stability of the closed-loop system during the control hold period.

[0055] Step S5: Under stable system conditions, apply the actual control law of the deadbeat prediction speed after the dynamic event trigger judgment in step S3. As the input to the current loop, the d-axis and q-axis reference voltages are generated after PI calculation in the current loop. , ,Will , After being converted into an inverter drive signal by the SVPWM module, it is applied to the permanent magnet synchronous motor.

[0056] This invention ultimately solves the problem of high online computational burden caused by the repeated calculation of control laws in each sampling period in traditional predictive speed control, and improves the stability of the control system while ensuring speed tracking performance.

[0057] Example 2 This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in Embodiment 1 above.

[0058] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0059] Example 3 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in Embodiment 1 above.

[0060] The computer-readable storage medium in this embodiment can be an internal storage unit of the terminal, such as the terminal's hard disk or memory; the computer-readable storage medium in this embodiment can also be an external storage device of the terminal, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc. equipped on the terminal; furthermore, the computer-readable storage medium can include both the terminal's internal storage unit and external storage devices.

[0061] The computer-readable storage medium of this embodiment is used to store computer programs and other programs and data required by the terminal. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0062] Example 4 This embodiment provides a computer program product including computer-executable instructions stored on a machine-readable storage medium (such as a disk, flash memory, or optical disk). When executed by at least one data processing device (such as a microprocessor or digital signal processor), the instructions cause the data processing device to implement the steps in the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors.

[0063] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0064] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0066] The above description is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A dynamic event-triggered deadbeat predictive speed control method for a permanent magnet synchronous motor, characterized in that, Includes the following steps: Step S1: Establish the mechanical motion equations of the permanent magnet synchronous motor (PMSM) and obtain a discrete model of the PMSM's mechanical angular velocity through discretization to construct the speed tracking error. ,right The velocity tracking error at the next moment is derived and then organized into the standard velocity tracking error system form. Step S2: Calculate the ideal control law for deadbeat predictive speed control based on the standard speed tracking error system form obtained in Step S1, using the disturbance estimate. Replace the real disturbance in the ideal control law Thus, the actual control law for deadbeat predictive speed control is obtained; Step S3: For the actual control law in step S2, set the dynamic event triggering condition as follows. ,in, For dynamically triggered variables, For the trigger parameters, if the dynamic event triggering conditions are met, the new actual control law is recalculated and output; otherwise, the actual control law at the previous triggering moment remains unchanged, and the dynamic trigger variable is set. The update law is ,in, The attenuation coefficient is, and , Historical error weighting coefficients, It is a non-negative compensation term, and , For the first The square of the velocity tracking error at the next trigger moment; Step S4, based on and Construct a composite Lyapunov function and perform stability analysis on both the triggering time and the non-triggering interval; Step S5: Under stable system conditions, the actual control law of the deadbeat prediction speed after dynamic event trigger judgment in step S3 is applied. As the input to the current loop, the d-axis and q-axis reference voltages are generated after PI calculation in the current loop. , ,Will , After being converted into an inverter drive signal by the SVPWM module, it is applied to the permanent magnet synchronous motor.

2. The dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1, characterized in that, In step S1, the prediction expression for the velocity tracking error at the next moment is: ； In the formula, for Velocity tracking error at sampling time for Velocity tracking error at sampling time For the moment of inertia of the motor, The coefficient of viscous friction, for Load torque at the sampling time The sampling period is This is the torque coefficient of the permanent magnet synchronous motor. for The q-axis component of the stator current at the sampling time. Sampling time, Given a mechanical angular velocity; The prediction expression for the next-moment velocity tracking error in the standard velocity tracking error system form is: ； In the formula, Let be the speed tracking error coefficient, where , Let be the control law coefficient, where , for Control law at sampling time, This is the system's actual disturbance term, which includes load torque and reference input related terms. 。 3. The dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 2, characterized in that, In step S2, by ensuring that the speed tracking error is zero at the next moment in the form of a standard speed tracking error system, the ideal control law for deadbeat predictive speed control is obtained. The calculation formula for the ideal control law is as follows: ； In the formula, For ideal control laws; Using disturbance estimates Replace the real disturbance in the ideal control law The actual control law is obtained, and the formula for calculating the actual control law is as follows: ； In the formula, for The disturbance estimate at the sampling time.

4. The dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1, characterized in that, In step S3, the calculation formula for the actual control law is as follows: ； In the formula, The control law is calculated by the predictive controller at the current moment. For the first Control law at the next trigger moment For the first Next trigger moment For the trigger parameters, where, , This is a dynamically triggered variable.

5. The dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1, characterized in that, In step S4, the formula for calculating the composite Lyapunov function is as follows: ； In the formula, for k Composite Lyapunov functions at sampling time, These are the weighting coefficients, and .

6. The dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1, characterized in that, In step S4, within the non-trigger interval, the composite Lyapunov function satisfies the linear recursion inequality. ,in, The recursive contraction coefficient is, and , The nonnegative constant is determined by the perturbation estimation bias, the bounded perturbation, and the nonnegative compensation term. Iterating through this inequality, we can see that... It will not grow indefinitely with the number of sampling steps; at this point, the difference of the composite Lyapunov function is compressed to a value derived from... Within the defined scope, and because The speed tracking error remains bounded within the non-triggering range, and the system is stable. At the triggering time, the composite Lyapunov function satisfies the compression inequality. ,in The composite Lyapunov function value at the time preceding the trigger. The composite Lyapunov function value at the time following the trigger. Let be the contraction coefficient at the trigger time, and , For the moment before triggering, After each trigger, the system contracts once, thus suppressing the growth of velocity tracking error, until the velocity tracking error eventually satisfies... This means that the speed tracking error remains bounded at the trigger moment, and the system is stable.

7. An electronic device, characterized in that, include: One or more processors; A memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1.

8. A computer-readable storage medium, characterized in that, It stores computer-executable instructions, which, when executed, are used to implement the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1.

9. A computer program product, characterized in that, The aforementioned computer program product includes computer-executable instructions that, when executed, implement the dynamic event-triggered deadbeat predictive speed control method for permanent magnet synchronous motors as described in claim 1.

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