Strong-robustness rotary motion control method for two-degree-of-freedom switched reluctance motor

Abstract

The invention discloses a two-degree-of-freedom switched reluctance motor strong-robustness rotation motion control method, which comprises the following steps of: designing a rotation speed loop of rotation motion into a first-order active disturbance rejection controller to obtain reference current of a current loop, and forming an original data sequence of a first-order univariate grey prediction model based on current of four continuous sampling points of each phase winding; and calculating the predicted current of the next sampling point of each phase winding, and selecting the optimal switching state in combination with the reference current, the predicted current of each phase winding and a cost function to realize the strong robust control of the rotation motion of the two-degree-of-freedom switched reluctance motor. According to the method, motor parameters are not needed in rotary motion rotating speed outer loop control and predictive current inner loop control, the robustness of the control method under system disturbance is greatly improved, and the method has good application prospects and engineering value.

Description

Technical Field

[0001] The invention relates to the field of strong robust rotation motion control of a two-degree-of-freedom switched reluctance motor, in particular to a strong robust rotation motion control method of a two-degree-of-freedom switched reluctance motor based on an auto-disturbance rejection controller and a grey prediction model. Background Art

[0002] The two-degree-of-freedom switched reluctance motor has the advantages of strong fault tolerance, multiple control parameters and flexible control methods. It has good application prospects in the fields of multi-degree-of-freedom motion such as automated control, instrument arm, and robot joints. Changes in the speed, inductance, load torque and other parameters of the two-degree-of-freedom switched reluctance motor will interfere with the normal operation of the motor and reduce the operating performance of the system. The traditional two-degree-of-freedom switched reluctance motor rotational motion control method improves the robustness of the single closed-loop control, which will greatly limit the overall improvement of the dual closed-loop robustness of the control method, and it is difficult to achieve the strong robust control performance of the two-degree-of-freedom switched reluctance motor rotational motion. Therefore, in order to avoid the influence of system disturbances on the rotational motion of the two-degree-of-freedom switched reluctance motor and achieve the strong robust control goal of the two-degree-of-freedom switched reluctance motor rotational motion control method, it is urgent to propose an effective solution. Summary of the invention

[0003] The purpose of the present invention is to provide a method for controlling the strong robust rotational motion of a two-degree-of-freedom switched reluctance motor in view of the problems existing in the prior art.

[0004] The technical solution proposed by the present invention is:

[0005] A method for controlling the rotational motion of a two-degree-of-freedom switched reluctance motor with strong robustness is characterized in that an anti-disturbance controller is designed based on a reference speed and an actual speed of the rotational motion to obtain a reference current, the actual current of each phase winding is obtained through a current sensor, the original data sequence consisting of the actual current of four consecutive sampling points of each phase winding is input into the designed first-order single variable grey prediction model to obtain the predicted current of each phase winding at the next sampling point, and the optimal switching state is selected in combination with the reference current, the predicted current of each phase winding and the cost function to realize the strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor.

[0006] A two-degree-of-freedom switched reluctance motor strong robust rotation motion control method of the present invention comprises the following steps:

[0007] Step 1: Design a tracking differentiator to generate a speed tracking signal;

[0008] Step 2: Design an extended state observer to estimate the speed and total disturbance of the two-degree-of-freedom switched reluctance motor rotation motion;

[0009] Step 3: Design a nonlinear error feedback control law to obtain a control signal reference current;

[0010] Step 4: Establish a first-order univariate grey prediction model to predict the current value of the next sampling point;

[0011] Step 5: Select the optimal switch state based on the reference current of the active disturbance rejection controller and the predicted current of the first-order single variable grey prediction model to achieve strong robust control of the rotation motion of the two-degree-of-freedom switched reluctance motor;

[0012] Furthermore, according to the mechanical equation of the two-degree-of-freedom switched reluctance motor , the electromagnetic torque formula Substituting this into the mechanical equation we get:

[0013]

[0014] In the formula, is the acceleration of the rotational motion of the two-degree-of-freedom switched reluctance motor; is the derivative of the motor inductance with respect to the rotor position angle; J is the moment of inertia; D is the viscous friction coefficient; ω is the rotation speed of the two-degree-of-freedom switched reluctance motor; i is the phase current of the two-degree-of-freedom switched reluctance motor; T L is the load torque; T e is the electromagnetic torque.

[0015] The outer loop of the rotating motion speed is designed as a first-order active disturbance rejection controller, and the corresponding first-order system state equation is:

[0016]

[0017] In the formula, u=i 2 ; is the acceleration of the rotational motion of the two-degree-of-freedom switched reluctance motor; f(t) is the total disturbance inside and outside the system; bu is the control quantity; y is the output signal; ω is the rotational speed of the two-degree-of-freedom switched reluctance motor.

[0018] When the current is low and the saturation of the inductor is not considered, dL / dθ can be regarded as a constant. K = dL / dθ is defined and the calculation formula of K is:

[0019]

[0020] Where, L max , L min is the maximum and minimum value of inductance; θ up is the inductance rising range.

[0021] The first-order ADRC is composed of three parts: tracking differentiator, extended state observer and nonlinear error feedback control law. The tracking differentiator is used to adjust the rotation speed ω of the two-degree-of-freedom switched reluctance motor. The input speed signal will output a smooth speed signal after passing through the tracking differentiator, and can quickly track the given speed. Given speed ω * Input into the tracking differentiator, and after passing through the differential tracker, a fast and smooth tracking signal z is obtained. 11 , the discrete expression of the tracking differentiator is:

[0022]

[0023] Where k is the kth sampling time point; ω * (k) is the speed setting value at time k; z 11 (k) and z 11 (k+1) are the speed tracking values ​​at time k and (k+1) respectively; e 1 is the speed tracking error at time k; T is the sampling period; r is the speed tracking factor; α 1 is a nonlinear factor; δ 1 is the filtering factor.

[0024] The fal nonlinear function has a filtering function, and the expression of the fal function is:

[0025]

[0026] In the formula, e is the error; α is the nonlinear factor; δ is the filtering factor;

[0027] The extended state observer inputs the actual rotation speed ω of the two-degree-of-freedom switched reluctance motor into the extended state observer, estimates the speed and disturbance of the rotation speed control system, and obtains the speed observation value z 21 and the total disturbance estimate z 22 , the discrete expression of the extended state observer is:

[0028]

[0029] Where ω(k) is the actual speed of the motor at time k; z 21 (k) and z 21 (k+1) are the estimated values ​​of the motor speed at time k and (k+1); z 22 (k) and z 22 (k+1) are the estimated values ​​of the total disturbance of the system at time k and (k+1) respectively; u(k) is the control signal after disturbance compensation at time k; e 2 is the estimation error at time k; T is the sampling period; β 1 and β 2is the gain parameter of the extended state observer; α 2 is a nonlinear factor; δ 2 is the filtering factor; b is the input coefficient of the system.

[0030] The nonlinear error feedback control law is to track the speed tracking signal z of the differentiator 11 , and the extended state observer to track the signal z 21 The estimated value of is subtracted, and the control signal u is obtained through the control law. 0 , the discrete expression of the nonlinear error feedback control law is:

[0031]

[0032] In the formula, z 11 (k) is the speed tracking signal value at time k; z 21 (k) is the estimated speed at time k; e 3 is the error at time k; u 0 (k) is the control signal at time k; λ is the feedback gain; α 3 is a nonlinear factor; δ 3 is the filtering factor.

[0033] The expression of the rotational motion control quantity of the two-degree-of-freedom switched reluctance motor is:

[0034]

[0035] In the formula, u 0 (k) is the control quantity obtained by the nonlinear control law at time k; u(k) is the final control quantity after disturbance compensation at time k; z 22 (k) is the estimated value of the total motor disturbance at time k; b is the input coefficient of the system.

[0036] The reference current expression of the rotational motion of the two-degree-of-freedom switched reluctance motor is:

[0037]

[0038] In the formula, i ref is the reference current; u is the final control signal output by the active disturbance rejection controller.

[0039] Furthermore, a first-order univariate grey prediction model is established according to the actual current of each phase winding to predict the current value of the next sampling point.

[0040] The original current sequence expression based on the actual current of the four sampling points of each phase winding is:

[0041] I (0) ={i (0) (1),i (0) (2),i(0) (3),…,i (0) (n)} (10)

[0042] In the formula, I (0) is the original current sequence; i (0) (n) is the actual current value of the corresponding sampling point of each phase winding of the switched reluctance motor.

[0043] The current accumulation generation sequence expression is:

[0044] I (1) ={i (1) (1),i (1) (2),i (1) (3),…,i (1) (n)} (11)

[0045] In the formula, I (I) is the current accumulation generation sequence;

[0046] Background value z (1) The calculation expression of (k) is:

[0047]

[0048] In the formula, i (1) (k-1) and i (1) (k) is the (k-1)th and kth current accumulation values ​​in a cumulative sequence; z (1) (k) is the kth background value.

[0049] According to the original current sequence I (0) and background value z (1) (k) The whitening equations of the prediction model are obtained as follows:

[0050]

[0051] In the formula, i (0) (2) i (0) (3) i (0) (n) are the original current sequence I (0) The second, third and nth current values ​​in z (1) (2) z (1) (3) z (1) (n) are the 2nd, 3rd and nth background values ​​respectively; a is the development coefficient; u is the gray effect degree.

[0052] The unknown parameters a and u in the whitening equation group are obtained by fitting using the least squares method. The least squares fitting formula is:

[0053]

[0054] In the formula, z (1) (k) is the kth background value; i (0) (k) is the kth current value in the original current sequence; a is the development coefficient; u is the gray effect; n is the number of currents in the original current sequence.

[0055] The first-order linear differential equation of formula (13) is:

[0056]

[0057] In the formula, i( 1 ) is the accumulated current value; a is the development coefficient; u is the gray effect degree.

[0058] The predicted current value at the (k+1)th moment of the current accumulation generation sequence is:

[0059]

[0060] In the formula, i (0) (1) is the first current value in the original current sequence; is the predicted value of the current accumulation sequence at time (k+1); a is the development coefficient; u is the grey effect degree.

[0061] The current prediction value at the (k+1)th moment of the original current sequence is:

[0062]

[0063] In the formula, is the original sequence current prediction value at the (k+1)th moment; i (0) (1) is the first data value in the original sequence; is the predicted value of the current accumulation sequence at the kth and (k+1th) moments; a is the development coefficient; u is the gray effect degree.

[0064] The original data sequence uses a sliding window to update the current data in real time. (0) The predicted value at the (k+1)th moment is obtained through the grey prediction model After that, remove the original sequence I (0) The first data value i in (0) (1), add the actual current value i at the (k+1)th moment (0) (k+1) constitutes a new original sequence I (0) new Calculate the current at the next sampling point (k+2) by using the grey prediction model And so on, dynamic prediction is achieved.

[0065] The cost function of the predicted current control of the two-degree-of-freedom switched reluctance motor rotation motion is:

[0066]

[0067] In the formula, i ref It is the reference current output by the first-order ADRC; It is the predicted current value at the (k+1)th moment predicted by the first-order univariate grey prediction model.

[0068] The reference current i output by the first-order anti-disturbance controller of the rotation speed outer loop of the two-degree-of-freedom switched reluctance motor is ref And the current prediction value at the (k+1)th moment output by the first-order univariate grey prediction model Substitute it into the value function to select the optimal switching state and realize strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor.

[0069] Beneficial effect: Due to the adoption of the above technical solution, the present invention is applicable to a method for controlling the rotational motion of a two-degree-of-freedom switched reluctance motor with strong robustness, which effectively solves the problem of low system robustness. The proportional-integral controller is replaced by a first-order anti-disturbance controller of the outer loop of the rotational motion speed, and the current is predicted by a gray prediction model of the inner loop of the current, all without relying on the specific parameters of the motor, and the internal and external disturbances of the motor are estimated and compensated in real time, thereby improving the robustness of the system. In addition, the reference current and the predicted current are substituted into the value function to select the optimal switching state, thereby realizing strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a block diagram of a two-degree-of-freedom switched reluctance motor strong robust rotation motion control method of the present invention.

[0071] Figure 2 It is a flow chart of sliding window design in the first-order single variable grey prediction model of the present invention.

[0072] Figure 3 It is a flow chart of a method for controlling the strong robust rotational motion of a two-degree-of-freedom switched reluctance motor according to the present invention. DETAILED DESCRIPTION

[0073] A real-time example of a three-phase 12 / 8 two-degree-of-freedom switched reluctance motor applicable to the present invention is further described below in conjunction with the accompanying drawings:

[0074] The mechanical equations of a two-degree-of-freedom switched reluctance motor are:

[0075]

[0076] In the formula, is the acceleration of the two-degree-of-freedom switched reluctance motor; J is the moment of inertia; D is the viscous friction coefficient; ω is the rotation speed of the two-degree-of-freedom switched reluctance motor; T e is the electromagnetic torque; T L is the load torque.

[0077] Electromagnetic torque torque formula Substituting into the mechanical equation we get:

[0078]

[0079] In the formula, is the acceleration of the rotational motion of the two-degree-of-freedom switched reluctance motor; is the derivative of the motor inductance with respect to the rotor position angle; J is the moment of inertia; D is the viscous friction coefficient; ω is the rotation speed of the two-degree-of-freedom switched reluctance motor; i is the phase current of the two-degree-of-freedom switched reluctance motor; T L is the load torque.

[0080] Figure 1 This is a block diagram of a two-degree-of-freedom switched reluctance motor strong robust rotation motion control method. According to the two-degree-of-freedom switched reluctance motor mechanical equation, the controlled system is described as a first-order active disturbance rejection controller, and the corresponding first-order system state equation is:

[0081]

[0082] In the formula, u=i 2 ; is the acceleration of the rotational motion of the two-degree-of-freedom switched reluctance motor; f(t) is the total disturbance inside and outside the system; bu is the control quantity; y is the system output; ω is the rotational speed of the two-degree-of-freedom switched reluctance motor.

[0083] When the current is low and the saturation of the inductor is not considered, dL / dθ can be regarded as a constant. K = dL / dθ is defined and the calculation formula of K is:

[0084]

[0085] Where, L max , L min is the maximum and minimum value of inductance; θ up is the inductance rising range.

[0086] The first-order active disturbance rejection controller is composed of three parts: tracking differentiator, extended state observer and nonlinear error feedback control law.

[0087] Figure 1TD is a tracking differentiator, which is used to adjust the rotation speed ω of the two-degree-of-freedom switched reluctance motor. The input speed ω will output a smooth speed signal z after passing through the tracking differentiator. 11 , and can quickly track the given speed. The discrete expression of the tracking differentiator is:

[0088]

[0089] Where k is the kth sampling time point; ω * (k) is the speed setting value at time k; z 11 (k) and z 11 (k+1) are the speed tracking values ​​at time k and (k+1) respectively; e 1 is the speed tracking error at time k; T is the sampling period; r is the speed tracking factor; α 1 is a nonlinear factor; δ 1 is the filtering factor.

[0090] The fal nonlinear function has a filtering function, and the expression of the fal function is:

[0091]

[0092] Where e is the error; α is the nonlinear factor; δ is the filtering factor.

[0093] Figure 1 ESO is an extended state observer, which is used to input the actual rotation speed ω of the two-degree-of-freedom switched reluctance motor into the extended state observer, estimate the speed and disturbance of the speed control system, and obtain the speed observation value z 21 and the total disturbance estimate z 22 , the discrete expression of the extended state observer is:

[0094]

[0095] Where ω(k) is the actual speed of the motor at time k; z 21 (k) and z 21 (k+1) are the estimated values ​​of the motor speed at time k and (k+1); z 22 (k) and z 22 (k+1) are the estimated values ​​of the total disturbance of the system at time k and (k+1) respectively; u(k) is the control signal after disturbance compensation at time k; e 2 is the estimation error at time k; T is the sampling period; β 1 and β 2 is the gain parameter of the extended state observer; α 2 is a nonlinear factor; δ 2is the filtering factor; b is the input coefficient of the system.

[0096] Figure 1 NLSEF is the nonlinear error feedback control law, which is used to track the speed tracking signal z of the differentiator. 11 , and the extended state observer to track the signal z 21 The estimated value of is subtracted and the control signal u is obtained through the control law. 0 , the discrete expression of the nonlinear error feedback control law is:

[0097]

[0098] In the formula, z 11 (k) is the speed tracking signal value at time k; z 21 (k) is the estimated speed at time k; e 3 is the error at time k; u 0 (k) is the control signal at time k; λ is the feedback gain; α 3 is a nonlinear factor; δ 3 is the filtering factor.

[0099] Combining the first-order system state equation (3) and the nonlinear control law formula (8), it can be found that the expression of the rotational motion control quantity of the two-degree-of-freedom switched reluctance motor is:

[0100]

[0101] In the formula, u 0 (k) is the control quantity obtained by the nonlinear control law at time k; u(k) is the final control quantity after disturbance compensation at time k; z 22 (k) is the estimated value of the total motor disturbance at time k; b is the input coefficient of the system.

[0102] From formula (3), we can see that the final control signal u=i 2 , the reference current expression of the two-degree-of-freedom switched reluctance motor rotation motion is:

[0103]

[0104] In the formula, i ref is the reference current; u is the final control signal output by the active disturbance rejection controller.

[0105] Figure 1 GM(1,1) is a first-order univariate grey prediction model, where GM stands for “grey model”, (1,1) indicates that the model is a first-order univariate differential equation model, the first 1 indicates a first-order cumulative generation sequence, and the second 1 indicates that the model is a univariate model.

[0106] Figure 2Design flow chart for sliding window in first-order univariate grey prediction model. Sliding window establishment method: For the original sequence I (0) Perform an accumulation to get I (1) Establish a grey prediction model to obtain the predicted value at time (k+1) ; Then remove the original sequence I (0) i (0) (1), add the actual current value i at time (k+1) (0) (k+1) constitutes a new original sequence I (0) new The grey prediction model is calculated, and so on, to achieve dynamic prediction. (0) The data in is updated in real time, and the predicted value Also updated in real time.

[0107] Furthermore, a first-order univariate grey prediction model is established according to the actual current of each phase winding to predict the current value of the next sampling point.

[0108] The original current sequence expression based on the actual current of the four sampling points of each phase winding is:

[0109] I (0) ={i (0) (1),i (0) (2),i (0) (3),…,i (0) (n)} (11)

[0110] In the formula, I (0) is the original current sequence; i (0) (n) is the actual current value of the corresponding sampling point of each phase winding of the switched reluctance motor.

[0111] The current accumulation generation sequence expression is:

[0112] I (1) ={i (1) (1),i (1) (2),i (1) (3),…,i (1) (n)}(12)

[0113] In the formula, I (1) is the current accumulation generation sequence;

[0114] Background value z (1) The calculation expression of (k) is:

[0115]

[0116] In the formula, i (1)(k-1), i (1) (k) are the (k-1)th and kth current accumulation values ​​in a cumulative sequence; z (1) (k) is the kth background value.

[0117] According to the original current sequence I (0) and background value z (1) (k) The whitening equations of the prediction model are:

[0118]

[0119] In the formula, i (0) (2) i (0) (3) i (0) (n) are the original current sequence I (0) The second, third and nth current values ​​in z (1) (2) z (1) (3) z (1) (n) are the 2nd, 3rd and nth background values ​​respectively; a is the development coefficient; u is the gray effect degree.

[0120] The unknown parameters a and u in the whitening equation group are obtained by fitting using the least squares method. The least squares fitting formula is:

[0121]

[0122] In the formula, z (1) (k) is the kth background value; i (0) (k) is the kth current value in the original current sequence; a is the development coefficient; u is the gray effect; n is the number of currents in the original current sequence.

[0123] The first-order linear differential equation of formula (14) is:

[0124]

[0125] In the formula, i (1) The primary accumulated current value; a is the development coefficient; u is the gray effect degree.

[0126] The predicted current value at the (k+1)th moment of the current accumulation generation sequence is:

[0127]

[0128] In the formula, i (0) (1) is the first current value in the original current sequence; is the predicted value of the current accumulation sequence at time (k+1); a is the development coefficient; u is the grey effect degree.

[0129] The current prediction value at the (k+1)th moment of the original current sequence is:

[0130]

[0131] In the formula, is the original sequence current prediction value at the (k+1)th moment; i (0) (1) is the first data value in the original sequence; is the predicted value of the current accumulation sequence at the kth and (k+1th) moments; a is the development coefficient; u is the gray effect degree.

[0132] The cost function of the predicted current control of the two-degree-of-freedom switched reluctance motor rotation motion is:

[0133]

[0134] In the formula, i ref It is the reference current output by the first-order ADRC; It is the predicted current value at the (k+1)th moment predicted by the first-order univariate grey prediction model.

[0135] Furthermore, the reference current i output by the first-order anti-disturbance controller of the rotation speed outer loop of the two-degree-of-freedom switched reluctance motor is ref And the current prediction value at the (k+1)th moment output by the first-order univariate grey prediction model Substitute it into the value function to select the optimal switching state and realize strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor.

[0136] Figure 3 This is a flow chart of a method for controlling the strong robust rotational motion of a two-degree-of-freedom switched reluctance motor. When the two-degree-of-freedom switched reluctance motor is operating normally, the given rotational speed and the actual rotational speed are input into the anti-disturbance controller, the reference current value required by the current inner loop is calculated, and then the current of each phase winding is predicted using the grey prediction current control method. The reference current and the predicted current are substituted into the evaluation function to select the optimal switching state, thus realizing strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor.

[0137] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should fall within the protection scope of the technical scheme of the present invention.

Claims

1. A method for controlling the robust rotational motion of a two-degree-of-freedom switched reluctance motor, characterized in that: Based on the reference speed and actual speed of the rotational motion, an anti-disturbance controller is designed to obtain the reference current. The actual current of each phase winding is obtained through a current sensor. The original data sequence consisting of the actual current of four consecutive sampling points of each phase winding is input into the designed first-order univariate grey prediction model to obtain the predicted current of each phase winding at the next sampling point. The optimal switching state is selected by combining the reference current, the predicted current of each phase winding and the cost function to realize strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor.

2. The method for controlling the robust rotational motion of a two-degree-of-freedom switched reluctance motor according to claim 1 comprises the following steps: Step 1: Design a tracking differentiator to generate a speed tracking signal; Step 2: Design an extended state observer to estimate the speed and total disturbance of the two-degree-of-freedom switched reluctance motor rotation motion; Step 3: Design a nonlinear error feedback control law to obtain a control signal reference current; Step 4: Establish a first-order univariate grey prediction model to predict the current value of the next sampling point; Step 5: Select the optimal switch state based on the reference current of the active disturbance rejection controller and the predicted current of the first-order single variable grey prediction model to achieve strong robust control of the rotation motion of the two-degree-of-freedom switched reluctance motor; The specific operations of step 1 are: The rotation speed loop of the two-degree-of-freedom switched reluctance motor can be designed as a first-order active disturbance rejection controller; the first-order active disturbance rejection controller consists of three parts: tracking differentiator, extended state observer, and nonlinear state error feedback control law; The two-degree-of-freedom switched reluctance motor rotates at a given speed ω * Input into the tracking differentiator to obtain a smooth and fast speed tracking signal z 11 , the discrete expression of the tracking differentiator is: Where k is the kth sampling time point; ω * (k) is the speed setting value at time k; z 11 (k) and z 11 (k+1) are the speed tracking values ​​at time k and (k+1) respectively; e1 is the speed tracking error at time k; T is the sampling period; r is the speed tracking factor; α1 is the nonlinear factor; δ1 is the filtering factor; The fal nonlinear function has a filtering function, and the expression of the fal function is: In the formula, e is the error; α is the nonlinear factor; δ is the filtering factor; The specific operations of step 2 are: The actual rotation speed ω of the two-degree-of-freedom switched reluctance motor is input into the extended state observer, and the speed z in the speed control system is monitored in real time using the extended state observer. 21 and the total internal and external disturbance z 22 For observation estimation, the discrete expression of the extended state observer is: Where ω(k) is the actual speed of the motor at time k; z 21 (k) and z 21 (k+1) are the estimated values ​​of the motor speed at time k and (k+1); z 22 (k) and z 22 (k+1) is the estimated value of the total disturbance of the system at time k and (k+1) respectively; u(k) is the control signal after disturbance compensation at time k; e2 is the estimation error at time k; T is the sampling period; β1 and β2 are the gain parameters of the extended state observer; α2 is the nonlinear factor; δ2 is the filter factor; b is the input coefficient of the system; The specific operations of step 3 are: The speed tracking signal z 11 and the estimated speed z 21 Then, according to the nonlinear error feedback control law, the system control signal u0 is obtained. The discrete expression of the nonlinear error feedback control law is: In the formula, z 11 (k) is the speed tracking signal value at time k; z 21 (k) is the estimated speed at time k; u0(k) is the control signal at time k; e3 is the error at time k; λ is the feedback gain; α3 is the nonlinear factor; δ3 is the filter factor; The expression of the rotational motion control quantity of the two-degree-of-freedom switched reluctance motor is: Where u0(k) is the control quantity obtained by the nonlinear control law at time k; u(k) is the final control quantity after disturbance compensation at time k; z 22 (k) is the estimated value of the total disturbance of the motor at time k; b is the input coefficient of the system; The reference current expression of the rotational motion of the two-degree-of-freedom switched reluctance motor is: In the formula, i ref is the reference current; u is the final control signal output by the ADRC; The specific operations of step 4 are: The original current sequence expression based on the actual current of the four sampling points of each phase winding is: I (0) ={i (0) (1),i (0) (2),i (0) (3),…,i (0) (n)} (7) In the formula, I (0) is the original current sequence; i (0) (n) is the actual current value of the corresponding sampling point of each phase winding of the switched reluctance motor; The current accumulation generation sequence expression is: I (1) ={i (1) (1),i (1) (2),i (1) (3),…,i (1) (n)} (8) In the formula, I (1) is the current accumulation generation sequence; Background value z (1) The calculation expression of (k) is: In the formula, i (1) (k-1), i (1) (k) are the (k-1)th and kth current accumulation values ​​in the current accumulation generation sequence; z (1) (k) is the kth background value; According to the original current sequence I (0) and background value z (1) (k) The whitening equations of the prediction model are obtained as follows: In the formula, i (0) (2) i (0) (3) i (0) (n) are the original current sequence I (0) The second, third and nth current values ​​in z (1) (2) z (1) (3) z (1) (n) are the 2nd, 3rd and nth background values ​​respectively; a is the development coefficient; u is the gray effect degree; The unknown parameters a and u in the whitening equation group are obtained by fitting using the least squares method. The least squares fitting formula is: In the formula, z (1) (k) is the kth background value; i (0) (k) is the kth current value in the original current sequence; a is the development coefficient; u is the gray effect; n is the number of currents in the original current sequence; The first-order linear differential equation of formula (10) is: In the formula, i (1) is the accumulated current value in the current accumulation generation sequence; a is the development coefficient; u is the gray effect degree; The predicted current value at the (k+1)th moment of the current accumulation generation sequence is: In the formula, i (0) (1) is the first current value in the original current sequence; is the predicted value of the current accumulation sequence at the (k+1)th moment; a is the development coefficient; u is the gray action degree; The current prediction value at the (k+1)th moment of the original current sequence is: In the formula, is the original sequence current prediction value at the (k+1)th moment; i (0) (1) is the first data value in the original sequence; is the predicted value of the current accumulation sequence at the kth and (k+1th moments; a is the development coefficient; u is the gray action degree; The original data sequence uses a sliding window to update the current data in real time. (0) The predicted value at the (k+1)th moment is obtained through the grey prediction model After that, remove the original sequence I (0) The first data value i in (0) (1), add the actual current value i at the (k+1)th moment (0) (k+1) constitutes a new original sequence I (0) new Calculate the current at the next sampling point (k+2) by using the grey prediction model And so on, dynamic prediction is achieved; The specific operations of step 5 are: The cost function of the predicted current control of the two-degree-of-freedom switched reluctance motor rotation motion is: In the formula, i ref is the reference current output by the first-order ADRC; is the predicted value of the current at the (k+1)th moment predicted by the first-order univariate grey prediction model; The reference current i output by the first-order anti-disturbance controller of the rotation speed outer loop of the two-degree-of-freedom switched reluctance motor is ref And the current prediction value at the (k+1)th moment output by the first-order univariate grey prediction model Substitute it into the value function to select the optimal switching state and realize strong robust control of the rotational motion of the two-degree-of-freedom switched reluctance motor.

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