An agent-based asynchronous motor speed sliding mode control method

Abstract

The application provides a method for realizing asynchronous motor speed control by adopting a method combining double-loop agent and sliding mode control; a speed error integral sliding mode signal is formed by a speed error signal and an integral thereof, then ideal current signals of t-axis and m-axis are generated by nonlinear transformation combination, and double-axis current error signals are obtained by comparison with measured t-axis and m-axis current signals; then an agent model is established based on the double-axis current error signals, a high-gain proportional integral sliding mode control is adopted to establish a strong coupling relationship between the agent model state and the current error state; unknown uncertain information of the model is preliminarily estimated by using a sliding mode adaptive method; finally, a proportional integral type sliding mode signal is designed according to the agent model, and nonlinear high-gain transformation is adopted to superimpose adaptive control, so that the state of the agent model is stable and the motor can track the given speed signal, and the method has the advantages that the corresponding speed of large and small instruction signals is fast.

Description

Technical Field

[0001] This invention relates to the field of electric motors, and more specifically, to a sliding mode control method for the speed of an asynchronous motor based on an agent. Background Technology

[0002] Traditional asynchronous motors often employ PI or PID control, which suffers from insufficient response speed to large signals. Furthermore, increasing the control gain necessitates derivative control, requiring control based on the speed derivative or similar signals, thus increasing system damping. However, measuring derivative signals is difficult, resulting in low accuracy, and the installation and cost of measuring components present a series of practical and unresolved problems. While asynchronous motors using sliding mode control exhibit good speed response to large signals, they suffer from low accuracy, chattering, and steady-state error with small signals. Solving this often requires engineers to reduce the gain during design, which then leads to insufficient response speed for small signals. Based on these background factors, this invention proposes a surrogate-based sliding mode control method. This method couples the entire control process through a surrogate model and extensively employs integral sliding mode, avoiding the use and measurement of derivative signals. This improves control accuracy and reduces chatter, thus achieving a better balance between response speed to both large and small signals, making this invention highly practical in engineering applications.

[0003] It should be noted that the information in the background section above is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a sliding mode control method for asynchronous motor speed based on an agent, thereby overcoming the problem that the dynamic performance of asynchronous motor control cannot simultaneously take into account both large and small signals due to defects in related technologies.

[0005] According to one aspect of the present invention, a proxy-based sliding mode control method for asynchronous motor speed is provided, comprising the following five steps:

[0006] Step S10: Measure the angular velocity of the asynchronous motor rotor using a speed sensor, and record it as... The current signal in the three-phase stationary coordinate system of the asynchronous motor is measured using a sensor. Then, a general three-phase to two-phase transformation is used to obtain the current signal in the two-phase stationary coordinate system. Finally, a standard transformation from the two-phase stationary to the two-phase rotating coordinate system is used to obtain the two-phase rotating current signal, which are denoted as follows: , ,in For two-phase rotating t-axis current signals, It is a two-phase rotating m-axis current signal.

[0007] Step S20: The speed command signal of the asynchronous motor is compared with the angular velocity of the asynchronous motor rotor to obtain the speed error signal; then the integral sliding mode signal of the speed error is solved by integrating the speed error signal and the speed error; then the integral sliding mode signal of the speed error and its nonlinear transformation signal are combined to obtain the t-axis ideal current signal and the m-axis ideal current signal respectively, and compared with the corresponding two-phase rotating t-axis current signal and the two-phase rotating m-axis current signal to obtain the t-axis current error signal and the m-axis current error signal.

[0008] Step S30: Compare the t-axis current signal error signal with the t-axis surrogate model state signal to obtain the t-axis surrogate error signal, integrate it to obtain the t-axis surrogate error integral signal, and then combine them to obtain the t-axis surrogate error integral sliding mode signal; then solve the t-axis surrogate model state differential signal based on the two-phase rotating t-axis current signal, the t-axis surrogate coupled control term, and the t-axis direct control quantity, and further integrate it to obtain the t-axis surrogate model state signal; then solve the t-axis current adaptive rate signal based on the t-axis surrogate error integral sliding mode signal; and integrate it to obtain the t-axis current adaptive signal; then... The t-axis proxy error integral sliding mode signal is used, and a high-gain nonlinear feedback is employed to design a t-axis proxy coupling control term to achieve tight coupling between the t-axis proxy model state signal and the t-axis current signal error signal. Then, based on the t-axis proxy model state signal and its integral, a t-axis proxy state sliding mode signal is designed. Finally, based on the aforementioned t-axis current adaptive signal, t-axis proxy state sliding mode signal, and their nonlinear transformation signal, the t-axis direct control quantity is calculated to achieve convergence of the t-axis current error signal to zero and the t-axis proxy model state signal to zero, thereby enabling the two-phase rotating t-axis current signal to track the ideal t-axis current signal.

[0009] Step S40: Compare the m-axis current signal error signal with the m-axis surrogate model state signal to obtain the m-axis surrogate error signal, integrate it to obtain the m-axis surrogate error integral signal, and then combine them to obtain the m-axis surrogate error integral sliding mode signal; then solve the m-axis surrogate model state differential signal based on the two-phase rotating m-axis current signal, the m-axis surrogate coupled control term, and the m-axis direct control quantity, and further integrate it to obtain the m-axis surrogate model state signal; then solve the m-axis current adaptive rate signal based on the m-axis surrogate error integral sliding mode signal; and integrate it to obtain the m-axis current adaptive signal; then... The m-axis proxy error integral sliding mode signal is used, and a high-gain nonlinear feedback is employed to design an m-axis proxy coupling control term to achieve tight coupling between the m-axis proxy model state signal and the m-axis current signal error signal. Then, based on the m-axis proxy model state signal and its integral, an m-axis proxy state sliding mode signal is designed. Finally, based on the aforementioned m-axis current adaptive signal, m-axis proxy state sliding mode signal, and their nonlinear transformation signal, the m-axis direct control quantity is calculated to achieve convergence of the m-axis current error signal to zero and the m-axis proxy model state signal to zero, thereby enabling the two-phase rotating m-axis current signal to track the ideal m-axis current signal.

[0010] Step S50: Based on the t-axis direct control quantity and the m-axis direct control quantity, perform the inverse transformation from the general two-phase stationary to two-phase rotating coordinate system transformation in step S10, and the inverse transformation from three-phase to two-phase transformation. Then, send the obtained three-phase signal to the asynchronous motor to realize the speed control of the asynchronous motor.

[0011] In one exemplary embodiment of the present invention, the ideal current signal of the t-axis and the ideal current signal of the m-axis are obtained by combining the integral sliding mode signal of the rotational speed error and its nonlinear transformation signal, and compared with the corresponding two-phase rotating t-axis current signal and two-phase rotating m-axis current signal to obtain the t-axis current error signal and the m-axis current error signal, including:

[0012] ;

[0013] ;

[0014] ;

[0015] ;

[0016] ;

[0017] ;

[0018] in This is the speed command signal for the asynchronous motor. This is the rotational speed error signal; For the integral sliding mode signal of rotational speed error, For constant sliding mode parameters, This represents the integral over the time signal; For the ideal current signal along the t-axis, , These are constant control parameters; For m-axis ideal current signal, , These are constant control parameters; This is the t-axis current error signal. This is the m-axis current error signal.

[0019] In one exemplary embodiment of the present invention, the t-axis proxy error signal is obtained by comparing the t-axis current signal error signal with the t-axis proxy model state signal, and then integrated to obtain the t-axis proxy error integral signal. These are then combined to obtain the t-axis proxy error integral sliding mode signal. Next, the t-axis proxy model state differential signal is solved based on the two-phase rotating t-axis current signal, the t-axis proxy coupled control term, and the t-axis direct control quantity, and further integrated to obtain the t-axis proxy model state signal. Then, the t-axis current adaptive rate signal is solved based on the t-axis proxy error integral sliding mode signal and integrated to obtain the t-axis current adaptive signal. Based on the t-axis proxy error integral sliding mode signal, a high-gain nonlinear feedback is used to design the t-axis proxy coupled control term to achieve tight coupling between the t-axis proxy model state signal and the t-axis current signal error signal. Then, based on the t-axis proxy model state signal and its integral, the t-axis proxy state sliding mode signal is designed. Finally, based on the t-axis current adaptive signal, the t-axis proxy state sliding mode signal, and its nonlinear transformation signal, the t-axis direct control quantity is calculated, including:

[0020] ;

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] in The t-axis is used as the proxy model state signal, with an initial value of 0. For the t-axis proxy error signal, The t-axis proxy error integral signal, The sliding mode signal is used as the agent for the t-axis error integration. , These are constant sliding mode parameters; The t-axis proxy coupling control term is initialized to 0. This is a direct control quantity for the t-axis, with an initial value of 0. The t-axis is the surrogate model state differential signal; This is the t-axis current adaptive rate signal; This is an adaptive signal for the t-axis current. This is a constant adaptive parameter used to adjust the convergence rate of the t-axis adaptive signal; For the t-axis high-gain nonlinear feedback term, For t-axis proxy coupling control terms; , A constant high gain coefficient; For the integral of the state signal of the surrogate model along the t-axis, The sliding mode signal is the proxy state signal for the t-axis; , These are constant control parameters for the direct control quantity of the t-axis.

[0030] In one example embodiment of the present invention, the m-axis current signal error signal is compared with the m-axis surrogate model state signal to obtain the m-axis surrogate error signal, which is then integrated to obtain the m-axis surrogate error integral signal. These are then combined to obtain the m-axis surrogate error integral sliding mode signal. Next, the m-axis surrogate model state differential signal is solved based on the two-phase rotating m-axis current signal, the m-axis surrogate coupled control term, and the m-axis direct control quantity is further integrated to obtain the m-axis surrogate model state signal. Then, the m-axis current adaptive rate signal is solved based on the m-axis surrogate error integral sliding mode signal and integrated to obtain the m-axis current adaptive signal. Based on the m-axis surrogate error integral sliding mode signal, a high-gain nonlinear feedback is used to design the m-axis surrogate coupled control term to achieve tight coupling between the m-axis surrogate model state signal and the m-axis current signal error signal. Based on the m-axis surrogate model state signal and its integral, the m-axis surrogate state sliding mode signal is designed. Finally, based on the m-axis current adaptive signal, the m-axis surrogate state sliding mode signal, and its nonlinear transformation signal, the m-axis direct control quantity is calculated, including:

[0031] ;

[0032] ;

[0033] ;

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] ;

[0039] ;

[0040] in The m-axis is used as the proxy model's state signal, with an initial value of 0. This is the m-axis proxy error signal. For the m-axis proxy error integral signal, The sliding mode signal is used as the agent for the error integration of the m-axis. , These are constant sliding mode parameters; The m-axis proxy coupling control term is initialized to 0. This is a direct control quantity for the m-axis, with an initial value set to 0. The m-axis surrogate model state differential signal; This is the m-axis current adaptive rate signal; This is an m-axis current adaptive signal. This is a constant adaptive parameter used to adjust the convergence rate of the m-axis adaptive signal; For m-axis high-gain nonlinear feedback term, For m-axis proxy coupling control terms; , A constant high gain coefficient; For the integral of the state signal of the m-axis proxy model, For the m-axis proxy state sliding mode signal; , These are constant control parameters for the direct control quantity of the m-axis.

[0041] Beneficial effects

[0042] This invention provides a proxy-based sliding mode control method for asynchronous motor speed, with the following four main innovations: First, it widely adopts integral sliding mode, avoiding the measurement of differential signals, especially speed differential signals, thereby reducing the requirements for measurement components in asynchronous motor control and lowering the overall economic cost. Second, it employs a combination of adaptive and sliding mode control, avoiding the need for precise asynchronous motor model parameters during proxy model establishment. This results in lower requirements for model parameters, making the solution universally applicable and suitable for situations where motor model parameters are uncertain or may drift during operation. Third, it uses proxy-based sliding mode control, coupling the relationship between speed and dual-axis current error through a proxy. This simplifies the design and enables a unified symmetrical design of the two loops, moving away from the linear decoupling design approach. This nonlinear direct design method provides more parameter selection space and better performance for motor control. Fourth, the proxy-based sliding mode control method allows the overall motor control performance to combine the advantages of fast response to large signals in sliding mode control with the excellent dynamic performance of small signal response in proxy control.

[0043] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0045] Figure 1 This is a flowchart of an asynchronous motor speed sliding mode control method based on an agent provided by the present invention;

[0046] Figure 2 This is a two-phase rotating t-axis current signal curve (unit: amperes) provided by the embodiment of the present invention.

[0047] Figure 3 This is a two-phase rotating m-axis current signal curve (unit: amperes) provided by the method in the embodiments of the present invention.

[0048] Figure 4 This is the angular velocity signal curve (unit: radians per second) of the asynchronous motor rotor provided by the method in the embodiments of the present invention.

[0049] Figure 5This is the rotational speed error signal curve (unit: radians per second) of the method provided in the embodiment of the present invention.

[0050] Figure 6 This is the ideal t-axis current signal (unit: amperes) provided by the method in the embodiments of the present invention.

[0051] Figure 7 This is the m-axis ideal current signal (unit: ampere) provided by the method in the embodiments of the present invention.

[0052] Figure 8 This is the t-axis current error signal (unit: amperes) provided by the method in the embodiments of the present invention.

[0053] Figure 9 This is the m-axis current error signal (unit: Ampere) provided by the method in the embodiments of the present invention.

[0054] Figure 10 It is the t-axis direct control quantity (unitless) of the method provided in the embodiments of the present invention.

[0055] Figure 11 It is the m-axis direct control quantity (unitless) of the method provided in the embodiments of the present invention.

[0056] Figure 12 This is the speed response curve (unit: radians per second) under the high speed command signal provided by the method in the embodiment of the present invention. Detailed Implementation

[0057] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make the invention more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of the invention. However, those skilled in the art will recognize that the technical solutions of the invention may be practiced with one or more of these specific details omitted, or other methods, components, apparatus, steps, etc., may be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the invention.

[0058] This invention provides a method for asynchronous motor speed control using a combination of dual-loop proxy and sliding mode control. First, a speed error integral sliding mode signal is formed from the speed error signal and its integral. Then, a nonlinear transformation is performed to generate ideal current signals for the t-axis and m-axis, which are compared with the measured transformed t-axis and m-axis current signals to obtain the dual-axis current error signal. Next, a proxy model is established based on the dual-axis current error signal, and a high-gain proportional-integral sliding mode control is used to establish a strong coupling relationship between the proxy model state and the current error state. Then, a sliding mode adaptive method is used to initially estimate the unknown and uncertain information of the model. Finally, a proportional-integral sliding mode signal is designed based on the proxy model, and a nonlinear high-gain transform superimposed adaptive control is used to achieve state stability and convergence of the proxy model. This enables the dual-axis current signal to track the ideal current signal, thereby achieving rapid and stable tracking of the motor to a given speed signal. This method has the advantage of fast response speed to both large and small command signals, and it combines the advantages of traditional PID control and sliding mode control. Furthermore, the introduction of integral sliding mode results in a small steady-state speed error and avoids the measurement of differential signals, reducing the requirements and economic costs of measurement components.

[0059] The following is a further explanation and description of the agent-based sliding mode control method for asynchronous motor speed according to the present invention. (Reference) Figure 1 As shown, this agent-based asynchronous motor speed sliding mode control method includes the following steps:

[0060] Step S10: Measure the angular velocity of the asynchronous motor rotor using a speed sensor, and record it as... The current signal in the three-phase stationary coordinate system of the asynchronous motor is measured using a sensor. Then, a general three-phase to two-phase transformation is used to obtain the current signal in the two-phase stationary coordinate system. Finally, a standard transformation from the two-phase stationary to the two-phase rotating coordinate system is used to obtain the two-phase rotating current signal, which are denoted as follows: , ,in For two-phase rotating t-axis current signals, This is a two-phase rotating m-axis current signal;

[0061] Step S20: The speed command signal of the asynchronous motor is compared with the angular velocity of the asynchronous motor rotor to obtain the speed error signal; then, the integral sliding mode signal of the speed error is calculated by integrating the speed error signal and the speed error; finally, the integral sliding mode signal of the speed error and its nonlinear transformation signal are combined to obtain the t-axis ideal current signal and the m-axis ideal current signal, respectively, and compared with the corresponding two-phase rotating t-axis current signal and two-phase rotating m-axis current signal to obtain the t-axis current error signal and the m-axis current error signal as follows:

[0062] Specifically, this can be broken down into the following three steps. First, the speed command signal of the asynchronous motor is compared with the angular velocity of the asynchronous motor rotor to obtain the speed error signal. Then, based on the speed error signal and the integral of the speed error, the integral sliding mode signal of the speed error is calculated as follows:

[0063] ;

[0064] ;

[0065] in This is the speed command signal for the asynchronous motor. This is the rotational speed error signal; For the integral sliding mode signal of rotational speed error, For constant sliding mode parameters, This represents the integral over the time signal.

[0066] The second step involves combining the integral sliding mode signal of the rotational speed error with its nonlinear transformation signal to obtain the ideal current signal along the t-axis and the ideal current signal along the m-axis, as follows:

[0067] ;

[0068] ;

[0069] in For the ideal current signal along the t-axis, , These are constant control parameters; For m-axis ideal current signal, , These are constant control parameters.

[0070] The third step involves comparing the ideal t-axis current signal and the ideal m-axis current signal with the corresponding two-phase rotating t-axis current signal and the two-phase rotating m-axis current signal to obtain the t-axis current error signal and the m-axis current error signal, as follows:

[0071] ;

[0072] ;

[0073] in This is the t-axis current error signal. This is the m-axis current error signal.

[0074] Step S30: Compare the t-axis current signal error signal with the t-axis surrogate model state signal to obtain the t-axis surrogate error signal, integrate it to obtain the t-axis surrogate error integral signal, and then combine them to obtain the t-axis surrogate error integral sliding mode signal; then solve the t-axis surrogate model state differential signal based on the two-phase rotating t-axis current signal, the t-axis surrogate coupled control term, and the t-axis direct control quantity, and further integrate it to obtain the t-axis surrogate model state signal; then solve the t-axis current adaptive rate signal based on the t-axis surrogate error integral sliding mode signal; and integrate it to obtain the t-axis current adaptive signal; then... The t-axis proxy error integral sliding mode signal is used, and a high-gain nonlinear feedback is employed to design a t-axis proxy coupling control term to achieve tight coupling between the t-axis proxy model state signal and the t-axis current signal error signal. Then, based on the t-axis proxy model state signal and its integral, a t-axis proxy state sliding mode signal is designed. Finally, based on the aforementioned t-axis current adaptive signal, t-axis proxy state sliding mode signal, and their nonlinear transformation signal, the t-axis direct control quantity is calculated to achieve convergence of the t-axis current error signal to zero and the t-axis proxy model state signal to zero, thereby enabling the two-phase rotating t-axis current signal to track the ideal t-axis current signal.

[0075] Specifically, it can be broken down into the following six steps. Step 1: Compare the t-axis current signal error signal with the t-axis surrogate model state signal to obtain the t-axis surrogate error signal, integrate it to obtain the t-axis surrogate error integral signal, and then combine them to obtain the t-axis surrogate error integral sliding mode signal as follows:

[0076] ;

[0077] ;

[0078] in The t-axis is used as the proxy model state signal, with an initial value of 0. For the t-axis proxy error signal, The t-axis proxy error integral signal, The sliding mode signal is used as the agent for the t-axis error integration. , These are constant sliding mode parameters.

[0079] The second step involves solving for the differential state signal of the t-axis surrogate model based on the two-phase rotating t-axis current signal, the t-axis surrogate coupled control term, and the t-axis direct control quantity. Further integration is then performed to obtain the t-axis surrogate model state signal as follows:

[0080] ;

[0081] ;

[0082] in The t-axis proxy coupling control term is initialized to 0. This is a direct control quantity for the t-axis, with an initial value of 0. The t-axis is the surrogate model state differential signal.

[0083] The third step is to solve for the t-axis current adaptive rate signal based on the sliding mode signal of the t-axis proxy error integration; and to obtain the t-axis current adaptive signal by integration as follows:

[0084] ;

[0085] ;

[0086] in This is the t-axis current adaptive rate signal; This is an adaptive signal for the t-axis current. This is a constant adaptive parameter used to adjust the convergence rate of the t-axis adaptive signal.

[0087] Fourth, based on the sliding mode signal of the t-axis proxy error integral, a high-gain nonlinear feedback is used to design the t-axis proxy coupling control term as follows:

[0088] ;

[0089] in For the t-axis high-gain nonlinear feedback term, For t-axis proxy coupling control terms; , It is a constant high gain coefficient.

[0090] Fifth, based on the t-axis surrogate model state signal and its integral, design the t-axis surrogate state sliding mode signal as follows:

[0091] ;

[0092] in For the integral of the state signal of the surrogate model along the t-axis, This is the sliding mode signal for the t-axis proxy state.

[0093] Step 6: Based on the aforementioned t-axis current adaptive signal, t-axis proxy state sliding mode signal, and its nonlinear transformation signal, calculate the t-axis direct control quantity as follows:

[0094] ;

[0095] in , For constant control parameters of the t-axis directly controllable quantity. It is a direct control quantity for the t-axis.

[0096] Step S40: Compare the m-axis current signal error signal with the m-axis surrogate model state signal to obtain the m-axis surrogate error signal, integrate it to obtain the m-axis surrogate error integral signal, and then combine them to obtain the m-axis surrogate error integral sliding mode signal; then solve the m-axis surrogate model state differential signal based on the two-phase rotating m-axis current signal, the m-axis surrogate coupled control term, and the m-axis direct control quantity, and further integrate it to obtain the m-axis surrogate model state signal; then solve the m-axis current adaptive rate signal based on the m-axis surrogate error integral sliding mode signal; and integrate it to obtain the m-axis current adaptive signal; then... The m-axis proxy error integral sliding mode signal is used, and a high-gain nonlinear feedback is employed to design an m-axis proxy coupling control term to achieve tight coupling between the m-axis proxy model state signal and the m-axis current signal error signal. Then, based on the m-axis proxy model state signal and its integral, an m-axis proxy state sliding mode signal is designed. Finally, based on the aforementioned m-axis current adaptive signal, m-axis proxy state sliding mode signal, and their nonlinear transformation signal, the m-axis direct control quantity is calculated to achieve convergence of the m-axis current error signal to zero and the m-axis proxy model state signal to zero, thereby enabling the two-phase rotating m-axis current signal to track the ideal m-axis current signal.

[0097] Specifically, it can be broken down into the following six steps. Step 1: Compare the m-axis current signal error signal with the m-axis surrogate model state signal to obtain the m-axis surrogate error signal, integrate it to obtain the m-axis surrogate error integral signal, and then combine them to obtain the m-axis surrogate error integral sliding mode signal as follows:

[0098] ;

[0099] ;

[0100] in The m-axis is used as the proxy model's state signal, with an initial value of 0. This is the m-axis proxy error signal. For the m-axis proxy error integral signal, The sliding mode signal is used as the agent for the error integration of the m-axis. , These are constant sliding mode parameters.

[0101] The second step involves solving for the state differential signal of the m-axis surrogate model based on the two-phase rotating m-axis current signal, the m-axis surrogate coupled control term, and the m-axis direct control quantity. Further integration is then performed to obtain the m-axis surrogate model state signal as follows:

[0102] ;

[0103] ;

[0104] in The m-axis proxy coupling control term is initialized to 0. This is a direct control quantity for the m-axis, with an initial value set to 0. The m-axis is the state differential signal of the proxy model.

[0105] The third step is to solve for the m-axis current adaptive rate signal based on the sliding mode signal of the m-axis proxy error integral; and to obtain the m-axis current adaptive signal by integration as follows:

[0106] ;

[0107] ;

[0108] in This is the m-axis current adaptive rate signal; This is an m-axis current adaptive signal. This is a constant adaptive parameter used to adjust the convergence rate of the m-axis adaptive signal.

[0109] Fourth, based on the sliding mode signal of the m-axis proxy error integral, a high-gain nonlinear feedback is used to design the m-axis proxy coupling control term as follows:

[0110] ;

[0111] in For m-axis high-gain nonlinear feedback term, For m-axis proxy coupling control terms; , It is a constant high gain coefficient.

[0112] Fifth, based on the m-axis surrogate model state signal and its integral, design the m-axis surrogate state sliding mode signal as follows:

[0113] ;

[0114] in For the integral of the state signal of the m-axis proxy model, This is the sliding mode signal for the m-axis proxy state.

[0115] Step 6: Based on the aforementioned m-axis current adaptive signal, m-axis proxy state sliding mode signal, and its nonlinear transformation signal, calculate the m-axis direct control quantity as follows:

[0116] ;

[0117] in , These are constant control parameters for the direct control quantity of the m-axis. It is a direct control quantity for the t-axis.

[0118] Step S50: Based on the t-axis direct control quantity and the m-axis direct control quantity, perform the inverse transformation from the general two-phase stationary to two-phase rotating coordinate system transformation in step S10, and the inverse transformation from three-phase to two-phase transformation. Then, send the obtained three-phase signal to the asynchronous motor to realize the speed control of the asynchronous motor.

[0119] Case Implementation and Analysis of Computer Solution Results

[0120] In step S10, the two-phase rotating t-axis current signals are obtained as follows: Figure 2 As shown, the two-phase rotating m-axis current signals are as follows: Figure 3 As shown, the angular velocity signal of the asynchronous motor rotor is obtained as follows: Figure 4 As shown.

[0121] In step S20, the speed command signal of the asynchronous motor is selected as 4 rad / s, and the speed error signal is obtained as follows: Figure 5 As shown. Select , , , , Obtain the ideal current signal along the t-axis, such as Figure 6 As shown, the ideal current signal along the m-axis is as follows: Figure 7 As shown, the t-axis current error signal is as follows: Figure 8 As shown, the m-axis current error signal is obtained as follows: Figure 9 As shown.

[0122] In step S30, select , , , , , , The direct control quantity of the t-axis is obtained as follows: Figure 10 As shown.

[0123] In step S40, select , , , , , , The direct control quantity of the m-axis is obtained as follows: Figure 11 As shown. Simultaneously, a high-speed command signal of 200 rad / s is set for the asynchronous motor; at this time, its angular velocity signal is as follows. Figure 12 As shown.

[0124] Depend on Figure 4 and Figure 12It can be seen that the entire asynchronous motor exhibits good dynamic characteristics to both high and low speed commands, and the rise time for both commands is approximately 0.15 to 0.2 seconds, indicating a relatively fast overall response speed. Figure 2 and Figure 3 It can be seen that the two-phase current of the motor ultimately remains constant, providing the current signal required to maintain the speed; while the current from the two phases of the motor remains constant. Figure 5 As can be seen, the speed error can smoothly converge to 0 without any chatter. This shows that the agent-based sliding mode speed control method provided by this invention is completely correct and effective, and has high engineering application value.

Claims

1. A proxy-based asynchronous motor speed sliding mode control method, characterized in that, The method comprises the following steps: Step S10, the angular velocity of the rotor of the asynchronous motor is measured by using a speed sensor, denoted as ; the current signals in the three-phase stationary coordinate system of the asynchronous motor are measured by using a sensor, then the current signals in the two-phase stationary coordinate system are obtained by using a general three-phase to two-phase conversion, and then the two-phase rotating current signals are obtained by using a standard two-phase stationary to two-phase rotating coordinate system conversion, and are respectively denoted as 、 , wherein is the two-phase rotating t-axis current signal, is the two-phase rotating m-axis current signal; Step S20, comparing the speed instruction signal of the asynchronous motor with the angular velocity of the rotor of the asynchronous motor to obtain a speed error signal; then obtaining a speed error integral sliding mode signal according to the speed error signal and the integral of the speed error; and then combining the speed error integral sliding mode signal and a nonlinear transformation signal thereof to obtain a t-axis ideal current signal and an m-axis ideal current signal, respectively, and comparing the t-axis ideal current signal and the m-axis ideal current signal with corresponding two-phase rotating t-axis current signals and two-phase rotating m-axis current signals to obtain a t-axis current error signal and an m-axis current error signal as follows: ； ； ； ； ； ； wherein is a speed command signal for an asynchronous motor, is a speed error signal; is a speed error integral sliding mode signal, is a constant sliding mode parameter, denotes integration over time; is a t-axis ideal current signal, , is a constant control parameter; is an m-axis ideal current signal, , is a constant control parameter; is a t-axis current error signal, is an m-axis current error signal; Step S30, comparing the t-axis current signal error signal with a t-axis agent model state signal to obtain a t-axis agent error signal, integrating the t-axis agent error signal to obtain a t-axis agent error integral signal, then combining the t-axis agent error integral signal to obtain a t-axis agent error integral sliding mode signal, then solving a t-axis agent model state differential signal according to the two-phase rotating t-axis current signal, a t-axis agent coupling control item and a t-axis direct control quantity, and further integrating the t-axis agent model state differential signal to obtain a t-axis agent model state signal; then solving a t-axis current adaptive rate signal according to the t-axis agent error integral sliding mode signal; and integrating the t-axis current adaptive rate signal to obtain a t-axis current adaptive signal; then using high-gain nonlinear feedback to design the t-axis agent coupling control item according to the t-axis agent error integral sliding mode signal, so as to realize close coupling between the t-axis agent model state signal and the t-axis current signal error signal; then designing a t-axis agent state sliding mode signal according to the t-axis agent model state signal and an integral of the t-axis agent model state signal; and then solving the t-axis direct control quantity according to the t-axis current adaptive signal, the t-axis agent state sliding mode signal and a nonlinear transformation signal of the t-axis agent state sliding mode signal, so as to realize convergence of the t-axis current error signal to zero and convergence of the t-axis agent model state signal to zero, thereby realizing tracking of the two-phase rotating t-axis current signal on the ideal t-axis current signal as follows: ； ； ； ； ； ； ； ； ； wherein is the t-axis agent model state signal, with an initial value of 0; is the t-axis agent error signal, is the t-axis agent error integral signal, is the t-axis agent error integral sliding mode signal, , is a constant sliding mode parameter; is the t-axis agent coupling control term, with an initial value of 0; is the t-axis direct control quantity, with an initial value of 0; is the t-axis agent model state differential signal; is the t-axis current adaptive rate signal; is the t-axis current adaptive signal, is a constant adaptive parameter, used to adjust the fast or slow convergence rate of the t-axis adaptive signal; is the t-axis high-gain nonlinear feedback term, is the t-axis agent coupling control term; , is a constant high-gain coefficient; is the integral of the t-axis agent model state signal, is the t-axis agent state sliding mode signal; , is a constant control parameter of the t-axis direct control quantity; Step S40, comparing the m-axis current signal error signal with an m-axis agent model state signal to obtain an m-axis agent error signal, integrating the m-axis agent error signal to obtain an m-axis agent error integral signal, then combining the m-axis agent error integral signal to obtain an m-axis agent error integral sliding mode signal, then solving an m-axis agent model state differential signal according to the two-phase rotating m-axis current signal, an m-axis agent coupling control item and an m-axis direct control quantity, and further integrating the m-axis agent model state differential signal to obtain an m-axis agent model state signal; then solving an m-axis current adaptive rate signal according to the m-axis agent error integral sliding mode signal; and integrating the m-axis current adaptive rate signal to obtain an m-axis current adaptive signal; then using high-gain nonlinear feedback to design the m-axis agent coupling control item according to the m-axis agent error integral sliding mode signal, so as to realize close coupling between the m-axis agent model state signal and the m-axis current signal error signal; then designing an m-axis agent state sliding mode signal according to the m-axis agent model state signal and an integral of the m-axis agent model state signal; and then solving the m-axis direct control quantity according to the m-axis current adaptive signal, the m-axis agent state sliding mode signal and a nonlinear transformation signal of the m-axis agent state sliding mode signal, so as to realize convergence of the m-axis current error signal to zero and convergence of the m-axis agent model state signal to zero, thereby realizing tracking of the two-phase rotating m-axis current signal on the ideal m-axis current signal as follows: ； ； ； ； ； ； ； ； ； wherein is the m-axis proxy model state signal, with an initial value of 0; is the m-axis proxy error signal, is the m-axis proxy error integral signal, is the m-axis proxy error integral sliding mode signal, , is a constant sliding mode parameter; is the m-axis proxy coupling control term, with an initial value of 0; is the m-axis direct control quantity, with an initial value of 0; is the m-axis proxy model state differential signal; is the m-axis current adaptive rate signal; is the m-axis current adaptive signal, is a constant adaptive parameter, used to adjust the fast or slow convergence rate of the m-axis adaptive signal; is the m-axis high-gain nonlinear feedback term, is the m-axis proxy coupling control term; , is a constant high-gain coefficient; is the integral of the m-axis proxy model state signal, is the m-axis proxy state sliding mode signal; , is a constant control parameter of the m-axis direct control quantity; Step S50, according to the t-axis direct control amount and m-axis direct control amount by step S10 in the general two-phase stationary to two-phase rotating coordinate system transformation inverse transformation, three-phase to two-phase transformation inverse transformation, then the resulting three-phase signal to asynchronous motor, so as to realize the speed control of asynchronous motor.

Images