Model-free coordinated adaptive optimal output regulator design method and control system

Abstract

The application discloses a model-free coordinated adaptive optimal output regulator design method and a control system. Firstly, a classic master-slave structure is adopted, torque synchronization is maintained through field-oriented control; then, a singular perturbation theory is applied to model order reduction of a double permanent magnet synchronous motor system, and a low-order model can effectively reduce learning time and calculation complexity of a speed loop controller design. Then, a model-free coordinated adaptive optimal output regulator is designed under an adaptive dynamic programming framework, so as to drive gear speed to asymptotically track a reference signal and inhibit bounded unknown load torque disturbance. The application can improve transient response performance.

Description

Technical Field

[0001] This invention relates to a model-free coordinated optimal output regulator design method and control system for dual permanent magnet synchronous motors based on adaptive dynamic programming, belonging to the field of permanent magnet synchronous motor control technology. Background Technology

[0002] In recent years, permanent magnet synchronous motors (PMSMs) have been widely used in servo drive systems that offer advantages such as high power density, compact structure, high torque-to-inertia ratio, maintenance-free operation, and low noise. These systems require fast response, a wide speed range, and high positioning accuracy. Researchers have proposed advanced control technologies for PMSMs, including model predictive control, fuzzy control, adaptive control, iterative learning control, active disturbance rejection control, and sliding mode control.

[0003] For permanent magnet synchronous motors (PMSMs) with input saturation and large load inertia variations, a speed control method based on fuzzy adaptive internal model was studied. A controller based on the internal model was designed using nonlinear output regulation theory to solve the speed and position tracking control problems respectively. These design methods have improved the performance of PMSMs to some extent. However, the above methods require mathematical model parameters of the PMSM, but these parameters are often inaccurate in engineering practice. This is because load torque disturbances, temperature fluctuations, and changes in operating point can all significantly affect the characteristics of PMSMs. Therefore, meaningful research on PMSMs with uncertain / unknown parameters is urgently needed.

[0004] The electrodynamics of permanent magnet synchronous motors change much faster than their corresponding mechanical dynamics. Therefore, rigidly connected dual permanent magnet synchronous motor systems exhibit pronounced dual-timescale characteristics. Due to the coexistence of fast and slow modes, mitigating the ill-conditioned numerical problems of such systems remains an ongoing research topic. Summary of the Invention

[0005] Objective: To maintain torque synchronization and improve transient response of a system, this invention proposes a model-free, coordinated, adaptive optimal output regulator design method and control system using field-oriented control, without requiring knowledge of system dynamics. More specifically, we begin with a mathematical model of a rigidly connected dual permanent magnet synchronous motor system. Then, using a classic master-slave control structure, we design an internal current proportional-integral controller. Based on singular perturbation theory algorithms, the dual permanent magnet synchronous motor model is simplified to include only the slow-speed component. To solve for the regulator, this invention proposes a model-based design scheme and a model-free adaptive dynamic programming design scheme. Finally, comprehensive experimental studies verify the performance of the proposed method and compare it with the traditional PI control method. The most important feature of this invention is the proposal of an optimal output regulation method based on an internal model, achieving asymptotic tracking of the ring gear speed and suppression of load torque disturbances.

[0006] Technical solution: To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0007] A model-free coordinated adaptive optimal output regulator design method includes the following steps:

[0008] Step 1: Establish a rigidly connected dual permanent magnet synchronous motor model based on the basic information of the permanent magnet synchronous motor.

[0009] Step 2: In the presence of uncertain / unknown parameters, a field-oriented control method is used to coordinate the control of the dual permanent magnet synchronous motor model to achieve torque synchronization and adjust the rotational speed of the paddle wheel to the reference signal, thereby improving the transient response.

[0010] Step 3, based on the coordinated control of the dual permanent magnet synchronous motor model, the design of the optimal speed output regulator is as follows:

[0011] Step 3.1, Design of a Model-Based Coordinated Optimal Speed ​​Output Regulator

[0012] Step 3.1 The design method of the model-based coordinated optimal speed output regulator is as follows:

[0013] To improve the transient response during speed regulation and enhance the overall performance of a rigidly connected dual permanent magnet synchronous motor system, the following optimal control problem is studied:

[0014]

[0015] The solution to this optimal control problem is:

[0016]

[0017] in, And matrix The following algebraic Riccati equations are satisfied:

[0018]

[0019] The current setpoint is designed as follows:

[0020]

[0021] Step 3.2, Design of a data-driven coordinated optimal speed regulator

[0022] The following equation is obtained by solving the model-free adaptive dynamic programming learning method. and :

[0023]

[0024] Through the obtained and The optimal output regulator is obtained.

[0025] Preferred method for establishing a rigidly connected dual permanent magnet synchronous motor model in step 1:

[0026] Step 1.1: Establish the permanent magnet synchronous motor based on its basic information. Dynamic model in coordinate system:

[0027]

[0028] The subscript k represents different sets of motor parameters, where k = 1 or 2. It is the rotor speed. and These are the direct-axis and quadrature-axis stator currents. and These are the direct-axis and quadrature-axis stator voltages. It is electromagnetic torque. It is rotor inertia. It is the coefficient of viscous friction. It is an extreme logarithm. It is the stator flux linkage. and These are direct-axis and quadrature-axis stator inductors. It is the load torque. It is the stator winding resistance.

[0029] Step 1.2, according to the torque equation of gear transmission:

[0030]

[0031] in, It is the reduction ratio of the gearbox. It is the radius of the pinion; for a ring gear, , , , and These are radius, load torque, coefficient of viscous friction, speed, and total inertia.

[0032] Step 1.3, based on the torque equation of gear transmission and the permanent magnet synchronous motor in... The dynamic model in coordinate system is obtained from the rigidly connected dual permanent magnet synchronous motor model:

[0033]

[0034] In the formula, , .

[0035] Preferred method for coordinated control of the dual permanent magnet synchronous motor model in step 2:

[0036] Step 2.1, this invention employs a magnetic field-oriented control strategy. The given value of the shaft current .exist After the shaft current tracks a given value, the model of the rigidly linked dual permanent magnet synchronous motor system simplifies to:

[0037]

[0038] To maintain torque synchronization, a master-slave structure is adopted, with both motors sharing a single speed controller. The output of the speed controller... It is used as the input to the quadrature current loops of the two motors. Simultaneously, optimal output regulation theory is utilized to adjust the speed and improve transient response. The coordinated control includes an internal PI controller for the current loop and an external optimal output regulator for the speed loop based on adaptive dynamic programming.

[0039] Step 2.2, Current Inner Loop Design

[0040] The current tracking error is:

[0041]

[0042] in, It is a reference value for the orthogonal current shared by the two motors.

[0043] Quadrature input voltage Select as:

[0044]

[0045] In the formula, It is proportional gain. It is integral gain. This is the integral of the error.

[0046] Will Substitute the simplified rigidly connected dual permanent magnet synchronous motor model, and combine it with the quadrature input voltage. The model is transformed to obtain the transformed rigidly connected dual permanent magnet synchronous motor model:

[0047]

[0048] In the formula, It has a small time constant.

[0049] Step 2.3, Model order reduction

[0050] The transformed rigidly connected dual permanent magnet synchronous motor model is set as follows: The quasi-steady state of the fast state variable is:

[0051]

[0052] Substituting the quasi-steady state of the fast state variables into the transformed rigidly connected dual permanent magnet synchronous motor model, we obtain the slow dynamic model of the rigidly connected dual permanent magnet synchronous motor:

[0053]

[0054] .

[0055] Preferably, the design method of the model-based coordinated optimal speed output regulator in step 3.1 is as follows:

[0056] Assuming a reference signal for gear speed Generated by the following systems

[0057]

[0058] in and It is an unknown constant matrix.

[0059] definition , The following output regulation problem is derived from the rigidly connected dual permanent magnet synchronous motor model:

[0060]

[0061] In the formula, control input Decision made ,and It is a speed control error and All of them are known matrices.

[0062] Under assumption 1: Under these conditions, speed regulation can be solved by using a feedback controller to address the output regulation problem:

[0063]

[0064] in, It is controllable. Characteristic polynomial and The same as the minimal polynomial.

[0065] When the output regulation problem reaches steady state under the control of the feedback controller, the steady-state variables are obtained:

[0066]

[0067] And there are:

[0068]

[0069] Transient variables:

[0070]

[0071] Therefore, we get:

[0072]

[0073] In the formula:

[0074] .

[0075] Preferably, the model-free adaptive dynamic programming learning method in step 3.2 is as follows:

[0076] Step 3.2.1, select an initial matrix. ,make It is Hurwitz stable, and a small parameter greater than zero is chosen. .

[0077] Step 3.2.2, at the time interval Internal use As input, where It is exploration noise.

[0078] Step 3.2.3, let .

[0079] Step 3.2.4, repeat steps 3.2.1-3.2.3.

[0080] Step 3.2.5, Solve and .

[0081] Step 3.2.6, let .

[0082] Step 3.2.7, until... .

[0083] Step 3.2.8 yields the optimal output regulator as follows: .

[0084] A dual permanent magnet synchronous motor control system, employing the aforementioned model-free coordinated adaptive optimal output regulator design method, includes two identical surface-mounted permanent magnet synchronous motors, a magnetic powder brake, and a torque sensor, wherein:

[0085] Each permanent magnet synchronous motor is equipped with an optical encoder and a gearbox. An external load is applied to the dual permanent magnet synchronous motor system through a magnetic powder brake. A torque sensor is mounted on the permanent magnet synchronous motor.

[0086] Preferably, the gearbox has a reduction ratio of 10.

[0087] Compared with the prior art, the present invention has the following advantages:

[0088] This invention employs a classic master-slave structure, maintaining torque synchronization through field-oriented control. Singular perturbation theory is applied to reduce the model order of the established dual permanent magnet synchronous motor system, resulting in a lower-order model that effectively reduces the learning time and computational complexity of the speed loop controller design. A model-free coordinated adaptive optimal output regulator is designed within an adaptive dynamic programming framework to drive the gear speed to asymptotically track the reference signal and suppress bounded unknown load torque disturbances. Using singular perturbation theory, the suboptimal performance and closed-loop stability of the controller under general standards are analyzed. Finally, experimental studies verify that the proposed control strategy can achieve speed tracking control and torque synchronization, while improving transient response performance. Attached Figure Description

[0089] Figure 1 This is a control system diagram of the optimal output regulator of the present invention.

[0090] Figure 2 It is a dual permanent magnet synchronous motor control system.

[0091] Figure 3 During the learning process and The convergence graph.

[0092] Figure 4 The figure shows the speed response of a dual permanent magnet synchronous motor under a model-free coordinated optimal regulation and control method based on adaptive dynamic programming.

[0093] Figure 5 The graph shows the actual speed and the error between the given speed of a dual permanent magnet synchronous motor under the model-free coordinated optimal regulation and control method based on adaptive dynamic programming.

[0094] Figure 6 The given current value is given for the dual permanent magnet synchronous motor under the model-free coordinated optimal regulation and control method based on adaptive dynamic programming.

[0095] Figure 7 The given current difference is given by the model-free coordinated optimal regulation and control method based on adaptive dynamic programming for a dual permanent magnet synchronous motor.

[0096] Figure 8This is the speed response of a dual permanent magnet synchronous motor under external disturbances, based on a model-free coordinated optimal regulation and control method using adaptive dynamic programming. Detailed Implementation

[0097] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the invention. After reading this invention, any modifications of the invention in various equivalent forms by those skilled in the art will fall within the scope defined by the appended claims.

[0098] A model-free coordinated optimal output regulator design method for dual permanent magnet synchronous motors based on adaptive dynamic programming, such as... Figure 1 As shown, it includes the following steps:

[0099] Step 1: Establish the mathematical model of the permanent magnet synchronous motor.

[0100] Step 1.1: Establish the permanent magnet synchronous motor based on its basic information. The dynamic model in coordinate system is described by the following equations.

[0101] (1)

[0102] In the formula, the subscript k (k=1, 2) represents different sets of motor parameters. It is the rotor speed. and These are the direct-axis and quadrature-axis stator currents. and These are the direct-axis and quadrature-axis stator voltages. It is electromagnetic torque. It is rotor inertia. It is the coefficient of viscous friction. It is an extreme logarithm. It is the stator flux linkage. and These are direct-axis and quadrature-axis stator inductors. It is the load torque. It is the stator winding resistance.

[0103] Based on the basic information of the permanent magnet synchronous motor and the torque transmission relationship between the gears, a rigid connection is established for the dual permanent magnet synchronous motors. The method of state equations in a coordinate system: The mathematical model of a rigidly connected dual permanent magnet synchronous motor includes the mathematical model of the permanent magnet synchronous motor and the torque equation of the gear transmission. Through coordinate transformation, the state equation of the rigidly connected dual permanent magnet synchronous motor in the coordinate system is obtained. The state equations in the coordinate system are as follows:

[0104]

[0105] In the formula, , . They are respectively shaft current, shaft current, shaft voltage, shaft voltage, For stator inductance, This is the resistance of the stator winding.

[0106] Step 1.2, based on the torque equation of gear transmission

[0107] (2)

[0108] in It is the reduction ratio of the gearbox. It is the radius of the pinion; for a ring gear, , , , and These are radius, load torque, coefficient of viscous friction, speed, and total inertia.

[0109] Combining this with the mathematical model of the permanent magnet synchronous motor from step 1.1, we obtain the rigidly connected dual permanent magnet synchronous motor model:

[0110] (3)

[0111] In the formula, , .

[0112] Step 2 proposes a coordinated control method in the presence of uncertain / unknown parameters, which can achieve torque synchronization, adjust the rotational speed of the planetary gear to the reference signal, and improve transient response.

[0113] Step 2.1, this invention employs a magnetic field-oriented control strategy. The given value of the shaft current .exist After the shaft current tracks a given value, the model of the rigidly linked dual permanent magnet synchronous motor system simplifies to:

[0114] (4)

[0115] To maintain torque synchronization, a master-slave structure is adopted, with both motors sharing a single speed controller. This means that the speed controller's output... It is used as the input to the quadrature current loops of the two motors. Simultaneously, optimal output regulation theory is utilized to adjust the speed and improve transient response. The proposed coordinated control consists of two main parts: an internal PI controller for the current loop and an external optimal output regulator for the speed loop based on adaptive dynamic programming.

[0116] Step 2.2, Current Inner Loop Design

[0117] The design incorporates an internal PI controller to regulate the quadrature current. Previously, we defined current tracking error as...

[0118] (5)

[0119] in, This is a reference value for the quadrature current shared by both motors. Quadrature input voltage. Select as

[0120] (6)

[0121] In the formula, It is proportional gain. It is integral gain. This is the integral of the error. Substituting into equation (4) and combining it with equation (5), the model can be transformed into...

[0122] (7)

[0123] In the formula, It has a small time constant because ,Increase It can Much smaller. In this case, It can facilitate the separation of time scales between electrodynamics and mechanical dynamics.

[0124] Step 2.3, Model order reduction

[0125] Clearly, (7) is a dual-timescale system with multiple small parameters. In this system, , The speed at which quasi-steady state is reached is much faster than and , Therefore, singular perturbation theory is employed to reduce the order of the magnetic field orientation model associated with the velocity loop. Furthermore, this helps to circumvent numerical stiffness in the analysis and synthesis of controller design.

[0126] Set equation (7) as The quasi-steady state of the fast state variable is

[0127] (8)

[0128] Substituting equation (8) into equation (7), we obtain the slow dynamics model of the rigidly connected dual permanent magnet synchronous motor.

[0129] (9)

[0130] The parameters in the formula are

[0131]

[0132] Step 3: Design of the optimal speed output regulator

[0133] Step 3.1, Design of a Model-Based Coordinated Optimal Speed ​​Output Regulator

[0134] Assuming a reference signal for gear speed Generated by the following systems

[0135] (10)

[0136] in and It is an unknown constant matrix.

[0137] definition , From equation (3), the following output regulation problem can be obtained.

[0138] (11)

[0139] In the formula, control input Decision made ,and It is a speed control error and All of them are known matrices.

[0140] Under assumption 1: Under the given conditions, speed regulation can be solved by the system (11) through the feedback controller.

[0141] (12)

[0142] in, It is controllable. Characteristic polynomial and The same as the minimal polynomial.

[0143] When the system (11) reaches steady state under the control of the controller (12), the steady-state variable can be obtained.

[0144] (13)

[0145] And there are

[0146] (14)

[0147] Based on the above equations, we can further define transient variables.

[0148] (15)

[0149] Then, through (11)-(15), we can obtain

[0150] (16)

[0151] In the formula

[0152]

[0153] To improve the transient response during speed regulation and enhance the overall performance of a rigidly connected dual permanent magnet synchronous motor system, the following optimal control problem is studied:

[0154] (17)

[0155] The solution to this optimal control problem is:

[0156] (18)

[0157] in, And matrix The following algebraic Riccati equations are satisfied

[0158] (19)

[0159] Therefore, the current setpoint is designed as follows:

[0160] (20)

[0161] Furthermore, if assumption 1 holds, then It is stable. According to optimal control theory, the solution to the algebraic Riccati equation is uniquely stable. Therefore, the closed-loop system matrix is... It is Herwitz stable.

[0162] However, the key to designing the optimal speed loop controller (20) is solving the algebraic Riccati equation (19), which typically relies on and The knowledge of rigidly connected dual permanent magnet synchronous motor systems is very difficult to implement in practice when the model parameters are uncertain / unknown.

[0163] Step 3.2, Design of a data-driven coordinated optimal speed regulator

[0164] In the absence of system model parameters, this invention designs an adaptive dynamic programming learning algorithm that solves the algebraic Riccati equation (19) iteratively using partial input and output data, and is used for the design of an external optimal speed regulator.

[0165] When the model parameters are unknown, they can be obtained by solving the following equations. and

[0166] (twenty one)

[0167] Algorithm 1 presents a model-free adaptive dynamic programming learning algorithm for approximating the optimal velocity loop controller (20). In practical applications, exploration noise... The rank condition can be guaranteed by using an exponentially decreasing signal, the sum of different sinusoidal signals, or random noise.

[0168]

[0169] A dual permanent magnet synchronous motor control system, such as Figure 2 As shown, a model-free coordinated adaptive optimal output regulator design method is adopted, including two identical surface-mounted permanent magnet synchronous motors, a magnetic powder brake, and a torque sensor, wherein:

[0170] Two identical surface-mounted permanent magnet synchronous motors (ACSM60-G00630LZ) were used. Their nominal parameters are shown in Table 1. Each permanent magnet synchronous motor was equipped with an optical encoder for precise rotor position measurement. Each motor also had a gearbox with a reduction ratio of 10. Because the two motors were axially connected, the experimental setup contained… The PMSM is a permanent magnet synchronous motor, and the MicroLabBox controller belongs to the dSPACE hardware system, suitable for the development of rapid control prototype systems. The software system of the rigid-flexible coupling multi-motor control experimental platform is mainly designed using three software programs: MATLAB / Simulink, Real-Time Interface (RTI), and ControlDesk. MATLAB / Simulink is primarily responsible for the design of the motor control algorithm. RTI is a real-time interface module library that configures all I / O interfaces graphically and processes the input and output signals of the MicroLabBox controller in real time. ControlDesk is the dSPACE comprehensive experimental and testing environment used for managing the measurement and control experimental process, enabling online adjustment of model parameters and the establishment of virtual instrument interfaces.

[0171] An external load is applied to the dual permanent magnet synchronous motor system using a magnetic powder brake (FZ-6-K), and a torque sensor is mounted on the permanent magnet synchronous motor. The torque sensor is a PK80G-10 model with an accuracy of 0.3%. The control algorithm is implemented using a multi-motor real-time experimental system based on dspace with a sampling frequency of 10 kHz.

[0172] Experimental data were acquired online via RTI (Real-Time Interface) and stored in the ControlDesk environment.

[0173] Table 1 Motor parameter settings

[0174] name <![CDATA[I N ]]> <![CDATA[U N ]]> <![CDATA[P N ]]> <![CDATA[n N ]]> <![CDATA[T LN ]]> <![CDATA[n k ]]> numerical values 1.5 220 200 3000 0.6 4 name <![CDATA[R k ]]> <![CDATA[L qk ]]> <![CDATA[L dk ]]> <![CDATA[J k ]]> numerical values 10.7 0.0098 0.0098 0.000021

[0175] Experimental results of a model-free coordinated optimal output regulator for a rigidly connected dual permanent magnet synchronous motor based on adaptive dynamic programming are as follows: Figures 3 to 8 As shown. Figure 3 for Figure 1 For the learning process and The convergence graph is formed by Figure 3 It can be seen that when the number of iterations reaches six, the system has basically reached a stable state. Figure 4 The image shows the speed response of a dual permanent magnet synchronous motor under a model-free coordinated optimal control method based on adaptive dynamic programming. Figure 5 The graph shows the actual speed and given speed error of a dual permanent magnet synchronous motor under a model-free coordinated optimal regulation and control method based on adaptive dynamic programming. Figure 6 Given the current value of a dual permanent magnet synchronous motor under a model-free coordinated optimal regulation and control method based on adaptive dynamic programming. Figure 7 The given current difference of the dual permanent magnet synchronous motor under the model-free coordinated optimal regulation and control method based on adaptive dynamic programming is given by... Figures 4-7 It can be seen that the rigid connection dual permanent magnet synchronous motor control system based on the model-free coordinated optimal regulation and control method of adaptive dynamic programming has fast tracking performance in both speed response and current curve, and has no steady-state error. Figure 8 To illustrate the speed response of a dual permanent magnet synchronous motor under external disturbances using a model-free coordinated optimal control method based on adaptive dynamic programming, the following is presented: Figure 8 As can be seen, when a sudden load is applied, the rotational speed fluctuates to some extent, but quickly recovers to the given speed, demonstrating the strong robustness of the closed-loop control system. It should be noted that the excellent performance exhibited in this example is for illustrative purposes only and not for limiting the scope of the invention.

[0176] The above describes a model-free coordinated optimal output regulator design method for a rigidly connected dual permanent magnet synchronous motor system based on adaptive dynamic programming. First, this invention employs a classic master-slave structure, maintaining torque synchronization through field-oriented control. Then, a reduced-order model of the dual permanent magnet synchronous motor system is established using singular perturbation theory, which is significant for reducing the learning time and computational complexity of the outer speed loop design. Next, a coordinated adaptive optimal output regulator is designed within the adaptive dynamic programming framework to drive the gear speed to asymptotically track the reference signal and adapt to load torque disturbances independent of system model parameter knowledge. Using singular perturbation theory, the suboptimal performance and closed-loop stability of the controller under mild conditions are analyzed. Finally, comprehensive experimental studies verify that the proposed control strategy can achieve speed regulation and torque synchronization, and improve transient response.

[0177] This invention simultaneously investigates the speed tracking and torque synchronization problems of a rigidly connected dual permanent magnet synchronous motor system with unknown model parameters. To maintain torque synchronization and improve the system's transient response, a coordinated adaptive optimal regulation design method is proposed using field-oriented control, without requiring knowledge of system dynamics. The control system exhibits numerous advantages, including fast dynamic response, small overshoot, and strong robustness to external disturbances.

[0178] 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 model-free coordinated adaptive optimal output regulator design method, characterized by, Comprising the following steps: Step 1, a rigidly connected double permanent magnet synchronous motor model is established according to the basic information of the permanent magnet synchronous motor; The method for establishing the rigidly connected double permanent magnet synchronous motor model: Step 1.1: Establish the permanent magnet synchronous motor based on its basic information. Dynamic model in coordinate system: Here, the subscript k represents different sets of motor parameters, k=1 or 2. It is the rotor speed. and These are the direct-axis and quadrature-axis stator currents. and These are the direct-axis and quadrature-axis stator voltages. It is electromagnetic torque. It is rotor inertia. It is the coefficient of viscous friction. It is an extreme logarithm. It is the stator flux linkage. and These are direct-axis and quadrature-axis stator inductors. It is the load torque. It is the stator winding resistance; Step 1.2, according to the gear torque equation: where, is the reduction ratio of the gearbox, is the radius of the pinion, for a ring gear, , , , and are the radius, load torque, viscous friction coefficient, velocity and total inertia, respectively. Step 1.3, the rigidly connected double permanent magnet synchronous motor model is obtained according to the torque equation of gear transmission and the dynamic model of permanent magnet synchronous motor in the coordinate wherein, , ;​ Step 2, in the presence of uncertain / unknown parameters, a field-oriented control method is used to coordinate control the double permanent magnet synchronous motor model, realize torque synchronization, adjust the wheel speed to the reference signal, and improve the transient response; Step 3, according to the design of the coordinated optimal speed output regulator in the coordinated control of the double permanent magnet synchronous motor model: Step 3.1, design of the model-based coordinated optimal speed output regulator Step 3.1 The design method of the model-based coordinated optimal speed output regulator is as follows: In order to improve the transient response in the speed regulation process and improve the overall performance of the rigidly connected dual permanent magnet synchronous motor system, the following optimal control problem is studied: The solution of the optimal control problem is: where and the matrix satisfies the following algebraic Riccati equation: The current given value is designed as: Step 3.2 The design of the data-based coordinated optimal speed regulator is obtained by solving the following equation through the model-free adaptive dynamic programming learning method and : The optimal output regulator is obtained by obtaining and .

2. The model-free coordinated adaptive optimal output regulator design method of claim 1, wherein, The method for coordinating control of the double permanent magnet synchronous motor model in step 2: Step 2.1, the magnetic field-oriented control strategy is adopted, Given value of shaft current ; in After the shaft current tracks the given value, the model of the rigidly linked dual permanent magnet synchronous motor system is simplified as: Keeping the torque synchronous, a master-slave structure is adopted, and the two motors share one speed regulator. The output of the speed regulator is used as the input of the quadrature current loops of the two motors; at the same time, the optimal output regulation theory is used to regulate the speed and improve the transient response; the coordinated control includes the internal PI controller of the current loop and the external optimal output regulator of the speed loop based on adaptive dynamic programming; Step 2.2, the current inner loop design current tracking error is: wherein, is the reference value of the quadrature current common to the two motors; the quadrature input voltage is selected as: wherein, is the proportional gain, is the integral gain, is the error integral; Will Substitute the simplified rigidly connected dual permanent magnet synchronous motor model, and combine it with the quadrature input voltage. The model is transformed to obtain the transformed rigidly connected dual permanent magnet synchronous motor model: In the formula, It has a small time constant; Step 2.3, model reduction: The transformed rigidly connected dual permanent magnet synchronous motor model is set to... The quasi-steady state of the fast state variable is: Substituting the quasi-steady state of the fast state variables into the transformed rigidly connected dual permanent magnet synchronous motor model, we obtain the slow dynamic model of the rigidly connected dual permanent magnet synchronous motor: .

3. The model-free coordinated adaptive optimal output regulator design method of claim 2, wherein, The method for designing the model-based coordinated optimal speed output regulator in step 3.1 is as follows: Assume the reference signal of gear speed Generated by the following system Where And Is an unknown constant matrix; define , The following output regulation problem is obtained from the model of rigidly connected dual permanent magnet synchronous motor: In the formula, the control input Determine And Speed control error and All are known matrices; under the condition of assumption 1: The speed regulation can be solved by the output regulation problem through the feedback controller: Where, Is controllable, The characteristic polynomial of Is the same as the minimum polynomial of When the output regulation problem reaches steady state under the control of the feedback controller, the steady state variable is obtained: And: Transient variable: Further: In the formula: .

4. The model-free coordinated adaptive optimal output regulator design method of claim 3, wherein, The model-free adaptive dynamic programming learning method in step 3.2 is as follows: step 3.2.1, selecting an initial matrix such that is Hurwitz stable, and selecting a small positive parameter ; Step 3.2.2, at time interval within the use as input, where is the exploration noise; Step 3.2.3, let ; Step 3.2.4, repeat Step 3.2.1 - Step 3.2.3; Step 3.2.5, solve and ; Step 3.2.6, let ; Step 3.2.7, until ; Step 3.2.8, resulting in the optimal output regulator as .

5. A dual permanent magnet synchronous motor control system, using the design method of model-free coordinated adaptive optimal output regulator of claim 1, characterized in that: It includes two identical surface-mounted permanent magnet synchronous motors, a magnetic powder brake, and a torque sensor, wherein: Each permanent magnet synchronous motor is equipped with an optical encoder, and the permanent magnet synchronous motor is equipped with a gearbox, an external load is applied to the double permanent magnet synchronous motor system through the magnetic powder brake, and the torque sensor is installed on the permanent magnet synchronous motor.

6. The dual permanent magnet synchronous machine control system of claim 5, wherein, The reduction ratio of the gearbox is 10.

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