Collaborative Predictive Control Method and System for Multi-Motor Drive Main Drive System of Rolling Mill

Abstract

This invention discloses a cooperative predictive control method and system for a multi-motor drive main transmission system of a rolling mill. The method includes acquiring the electromagnetic torque command values ​​of the drive motors under different roll speed errors, acquiring the stator flux linkage command values, observing the unknown disturbance terms of the d and q axes of the i-th drive motor, and using a preset flux linkage hyperlocal model predictive controller to obtain the control signal of the i-th drive motor based on the aforementioned state parameters. This invention can significantly improve the anti-interference capability and cooperative control performance of the multi-motor drive main transmission system of a rolling mill, effectively enhance the dynamic response and cooperative control accuracy of the rolling mill rolls, eliminate the influence of parameter mismatch on the precise cooperative control of the rolling mill rolls, and achieve high dynamic response and high-precision cooperative control of the multi-motor drive main transmission system of a rolling mill.

Description

Technical Field

[0001] This invention relates to the cooperative control technology of multi-motor systems in rolling mills, specifically to a cooperative predictive control method and system for the main drive system of multi-motor systems in rolling mills. Background Technology

[0002] Rolling mills are key equipment for rolling high-quality special steels such as large ship decks, high-pressure large-diameter oil and gas pipeline steel plates, thick plates for large pressure storage tanks, and electrical silicon steel. They represent a significant advancement in my country's rolling technology towards high-end applications. The main drive system is the core component of the rolling mill, enabling complex rolling processes, and its performance is crucial in determining the mill's rolling efficiency and quality. To meet my country's demand for high-quality special steels, higher requirements have been placed on the control precision and dynamic response of the rolling mill's main drive system. Traditional single-motor driven main drive systems require large gearboxes to adjust the speed of each roll, resulting in complex mechanical transmission structures, long speed adjustment times, poor control precision, low production efficiency, and high maintenance costs, which no longer meet the needs of modern metallurgical rolling processes. Multi-motor driven main drive systems for rolling mills adopt a novel structure where each roll is driven individually, eliminating the need for a large gearbox with complex mechanical transmission structures. This allows multiple motors to independently drive each roll, offering advantages such as fast response speed and high control precision, significantly improving the utilization rate of the rolling mill rolls. However, since each roll in the rolling mill is driven by an independent motor, a speed difference between the rolls during metallurgical rolling will cause cracks and ripples on the surface of the rolled steel, severely affecting the rolling efficiency and quality. Therefore, multi-motor drive system collaborative control technology is fundamental for rolling mills to complete complex rolling processes, and the current inner loop is key to achieving rapid response and high-precision collaborative control of the multi-motor drive system. Existing classic multi-motor system current inner loop control technologies mostly employ simple and easily implemented proportional-integral (PI) controllers. However, the moment the rolled steel enters the rolling mill rolls, it causes significant external disturbances to the drive motors. PI controllers designed based on steady-state operating points cannot achieve high dynamic response and high-precision collaborative control of the rolling mill rolls.

[0003] Predictive control (DC) is a high-performance control algorithm based on a discrete mathematical model of the controlled object. It boasts advantages such as fast dynamic response, simple algorithm implementation, high decoupling, and zero steady-state error, enabling rapid response and high-precision command tracking of multi-motor main drive systems as steel enters the rolls. However, currently, DC is primarily applied to servo motors, and no relevant literature or patent reports have been found regarding its application in multi-motor drive systems for rolling mills. Furthermore, to realize the application of DC in multi-motor drive systems for rolling mills, it is necessary to address the issue of coordinated control of the multi-motor drive system under predictive control and overcome the impact of parameter mismatch on precise coordinated control of the rolling mill rolls. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a cooperative predictive control method and system for a multi-motor driven main drive system of a rolling mill, which can significantly improve the anti-interference capability and cooperative control performance of the multi-motor driven main drive system of a rolling mill, effectively improve the dynamic response and cooperative control accuracy of the rolling mill rolls, eliminate the influence of parameter mismatch on the precise cooperative control of the rolling mill rolls, and realize high dynamic response and high-precision cooperative control of the multi-motor driven main drive system of a rolling mill.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0006] A cooperative predictive control method for a multi-motor drive main transmission system of a rolling mill includes:

[0007] 1) Based on the coordinated control instructions of the multi-motor drive system of the rolling mill The actual speed ω of the roll ei (k) and the average rotational speed ω between different rolls av (k) is used to obtain the electromagnetic torque command value of the drive motor under different roll speed errors. Based on the electromagnetic torque command value Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). Based on the real-time response speed ω of different rolls in the rolling mill ei (k) and the response current i of the drive motor dqi (k) is used to observe the unknown disturbance terms of the d and q axes of the i-th drive motor. and

[0008] 2) The controller predicts the electromagnetic torque command value using a pre-set flux hyperlocal model. Stator flux linkage command value Unknown disturbance terms on the d and q axes of the i-th drive motor and To obtain the control signal of the i-th drive motor.

[0009] Optionally, the preset flux hyperlocal model predictive controller in step 2) is based on the electromagnetic torque command value. Stator flux linkage command value Unknown perturbation term estimated by discrete flux sliding mode observer and The function expression for obtaining the control signal of the drive motor is:

[0010]

[0011] In the above formula, g swi ξ represents the switching information controlling the i-th drive motor.i These are the weighting coefficients. Let be the stator flux linkage command value for the i-th drive motor. Let be the electromagnetic torque command value for the i-th drive motor. and These are the stator flux linkage observations of the i-th drive motor along the d and q axes at time k+1, respectively, and n p ψ is the number of pole pairs of the drive motor. ro For permanent magnet flux linkage, L o Let be the inductance parameters of the drive motor, and we have:

[0012]

[0013] In the above formula, χ di and χ qi For hypermodel parameters, χ di =χ qi =-R o / L o R o T represents the resistance parameter of the drive motor. s To control the period, ψ di (k) and ψ qi (k) represents the stator flux linkages of the i-th drive motor along the d and q axes at time k, respectively, and u di (k) and u qi (k) represents the d-axis and q-axis stator voltages of the i-th drive motor at time k. and Let ε be the unknown disturbance terms of the d and q axes of the i-th drive motor at time k. di and ε qi Let ε be the parameter of the hypermodel to be designed. di =ε qi =1.

[0014] Optionally, step 2) is preceded by a step of designing a magnetic flux hyperlocal model predictive controller:

[0015] S1) The novel hyperlocal mathematical model of the magnetic flux linkage for the i-th driving permanent magnet motor is constructed as shown in the following equation:

[0016]

[0017] In the above formula, ψ di Let ψ be the stator flux linkage along the d-axis of the i-th drive motor. qi Let ω be the stator flux linkage on the q-axis of the i-th drive motor. ei Let i be the rotational speed of the i-th drive motor. di Let i be the d-axis current of the i-th drive motor. qi Let u be the q-axis current of the i-th drive motor. diLet u be the d-axis stator voltage of the i-th drive motor. qi Let u be the q-axis stator voltage of the i-th drive motor. di Let u be the d-axis stator voltage of the i-th drive motor. qi f is the q-axis stator voltage of the i-th drive motor. di For the mismatch term of the d-axis parameters of the i-th drive motor, f qi For the mismatch term of the q-axis parameter of the i-th drive motor, ψ ro For permanent magnet flux linkage, L o R is the inductance parameter of the drive motor. o Let Δψ be the resistance parameter of the drive motor. r χ represents the flux linkage variable after flux linkage parameter mismatch, and ΔL represents the inductance variable after inductance parameter mismatch. di and χ qi Let χ be the parameter of the hypermodel to be designed. di =χ qi =-R o / L o , ε di and ε qi The parameters of the hypermodel to be designed;

[0018] S2) Discretize the novel hyperlocal mathematical model of the i-th driving permanent magnet motor flux obtained by the construction, and then analyze the unknown disturbance term observations. and Substituting the values, we obtain the functional expressions for the stator flux linkages of the i-th drive motor at time k+1, which are shown in equation (2).

[0019] S3) Based on the function expression of the stator flux linkage observation values ​​of the i-th drive motor at time k+1 shown in Equation (2), the function expression of the flux linkage hyperlocal model predictive controller is designed as shown in Equation (1).

[0020] Optionally, in step 1), the electromagnetic torque command value of the drive motor under different roll speed errors is obtained. This is achieved through a speed controller based on synchronization error compensation. The speed controller includes a normal proportional-integral controller and an error-compensated proportional-integral controller. Furthermore, the speed controller based on synchronization error compensation acquires the electromagnetic torque command values ​​of the drive motor under different roll speed errors. This includes: coordinated control commands for the multi-motor drive system of the rolling mill. With the response speed ω of the rolls in the rolling mill ei The error of (k) is input to the proportional-integral controller under normal conditions to obtain the electromagnetic torque command value of different rolls in the rolling mill under normal conditions. The real-time response speed ω of different rolls in the rolling mill ei(k) and the average rotational speed ω between different rolls av The error of (k) is input to the error compensation proportional-integral controller to obtain the electromagnetic torque command value of different rolls in the rolling mill under the speed error. The electromagnetic torque command values ​​of different rolls in the rolling mill under normal conditions. Subtracting the speed error, the electromagnetic torque command value of different rolls in the rolling mill Obtain the electromagnetic torque command value of the drive motor under different roll speed errors.

[0021] Optionally, in step 1), the electromagnetic torque command value is... Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). This is achieved through the Maximum Torque-to-Current Ratio (MTPA) module, and the MTPA module transmits the electromagnetic torque command value. Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). The function expression is:

[0022]

[0023] In the above formula, ψ ro These are the flux linkage parameters of the rotor permanent magnet of the drive motor. n is the electromagnetic torque command value. p L represents the number of pole pairs of the drive motor. o These are the inductance parameters of the drive motor.

[0024] Optionally, in step 1), the unknown disturbance terms of the d and q axes of the i-th drive motor are observed. and This is achieved through a discrete flux linkage sliding mode observer, and the functional expression of the discrete flux linkage sliding mode observer is:

[0025]

[0026] In the above formula, the subscript i represents the drive motor corresponding to any roll in the rolling mill. Let be the observed value of the stator flux linkage on the d-axis of the i-th drive motor at time k+1. Let be the observed value of the stator flux linkage on the q-axis of the i-th drive motor at time k+1. Let k be the d-axis stator flux linkage observation value of the i-th drive motor. Let ψ be the observed value of the stator flux linkage on the q-axis of the i-th drive motor at time k. di (k) represents the actual value of the stator flux linkage on the d-axis of the i-th drive motor at time k, ψ qi (k) represents the actual value of the q-axis stator flux linkage of the i-th drive motor at time k, u di(k) represents the d-axis stator voltage of the i-th drive motor at time k, u qi (k) represents the q-axis stator voltage of the i-th drive motor at time k. Let k be the observed value of the unknown disturbance term on the d-axis of the i-th drive motor at time k. Let ρ be the observed value of the unknown disturbance term of the i-th drive motor on the q-axis at time k. di ρ is the real-time adjustment parameter for the d-axis of the i-th drive motor. qi T is the real-time adjustment parameter for the q-axis of the i-th drive motor. s To control the period, ν is a small constant greater than zero, and χ di and χ qi Let χ be the parameter of the hypermodel to be designed. di =χ qi =-R o / L o , ε di and ε qi Let ε be the parameter of the hypermodel to be designed. di =ε qi =1,L o R is the inductance parameter of the drive motor. o These are the resistance parameters of the drive motor.

[0027] Optionally, step 1) may be preceded by calculating the average rotational speed ω between the different rolls of the rolling mill. av (k) Step: Detect the real-time response speed ω of different rolls in the rolling mill. e1 (k), ω e2 (k), ω ei (k), ω en (k), where ω ei (k) represents the real-time response speed of the i-th roll in the rolling mill; based on the real-time response speed ω of different rolls in the rolling mill e1 (k), ω e2 (k), ω ei (k), ω en (k), calculate the average rotational speed ω between different rolls of the rolling mill. av (k).

[0028] Furthermore, the present invention also provides a cooperative predictive control system for a multi-motor driven main drive system of a rolling mill, comprising: a rolling mill roll speed detection unit for acquiring the actual speed ω of the rolls. ei (k) and the average rotational speed ω between different rolls av(k); Multi-motor system flux hyperlocal model cooperative controller, used to execute the steps of the cooperative predictive control method of the multi-motor drive main transmission system of the rolling mill, and output the obtained control signals of the drive motors to the control signal input terminal of each drive motor in the multi-motor drive main transmission system of the rolling mill; the output terminal of the rolling mill roll speed detection unit is connected to the input terminal of the multi-motor system flux hyperlocal model cooperative controller.

[0029] Furthermore, the present invention also provides a cooperative predictive control system for a multi-motor drive main transmission system of a rolling mill, including a microprocessor and a memory interconnected thereto, the microprocessor being programmed or configured to execute the steps of the cooperative predictive control method for the multi-motor drive main transmission system of the rolling mill.

[0030] Furthermore, the present invention provides a computer-readable storage medium storing a computer program for execution by a computer device to implement the cooperative predictive control method for the multi-motor drive main transmission system of the rolling mill.

[0031] Compared with the prior art, the present invention has the following main advantages:

[0032] 1. In the multi-motor drive main transmission system of the rolling mill, the current inner loop adopts magnetic flux super local cooperative predictive control to replace the traditional proportional integral control, which has the advantages of fast dynamic response speed and zero steady-state error tracking. It can realize the rapid response and high-precision command tracking of the multi-motor main transmission system at the moment when the rolled steel enters the roll.

[0033] 2. The magnetic flux super-local cooperative predictive control method of the multi-motor drive main transmission system of the rolling mill of the present invention has the advantages of strong robustness and simple control structure compared with other predictive control methods. It can specifically eliminate the influence of parameter mismatch on the precise cooperative control of the rolling mill rolls and effectively prevent the phenomenon of cracks and ripples on the surface of rolled steel caused by the difference in the speed of the rolling mill rolls. Attached Figure Description

[0034] Figure 1 This is a schematic diagram illustrating the working principle of the multi-motor drive main transmission system for rolling mills in an embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of the basic process of the method in an embodiment of the present invention.

[0036] Figure 3 The block diagram for implementing the collaborative predictive controller of the superlocal model of the magnetic flux linkage of the multi-motor system for the i-th roll is shown.

[0037] Figure 4 This is a block diagram illustrating the implementation of the superlocal cooperative predictive control method for the magnetic flux linkage of the multi-motor drive main transmission system of a rolling mill according to the present invention.

[0038] Figure 5The simulation diagram shows the roll synchronization error of a six-roll mill after applying the method of this invention. Detailed Implementation

[0039] The working principle diagram of the multi-motor drive main transmission system of the rolling mill in this embodiment is as follows: Figure 1 As shown, the multi-motor drive main transmission system of the rolling mill adopts a novel structure of individual transmission for each rolling mill roll, eliminating the need for a large gearbox with a complex mechanical transmission structure. Each roll is directly driven by a drive motor, as shown below. Figure 1 Table 1 shows the correspondence between the rolling mill rolls and the drive motors, that is, n drive motors independently drive n rolls. Figure 1 The intermediate mill roll speed detection unit 2 is used to detect the speed of each roll in the mill and obtain the average speed between each roll based on the speed of each roll. The speed of each roll and the average speed between each roll are input to the multi-motor system flux hyperlocal model cooperative controller 3 to obtain control signals for each drive motor, thereby achieving high-performance control of the multi-motor drive main transmission system of the mill. The main objective of the multi-motor system flux hyperlocal model cooperative controller is to improve the dynamic response performance and cooperative control accuracy of each roll in the mill, eliminate speed differences between the rolls, and prevent cracks and ripples on the surface of the rolled steel.

[0040] like Figure 2 As shown, the cooperative predictive control method for the multi-motor drive main transmission system of the rolling mill in this embodiment includes:

[0041] 1) Based on the coordinated control instructions of the multi-motor drive system of the rolling mill The actual speed ω of the roll ei (k) and the average rotational speed ω between different rolls av (k) is used to obtain the electromagnetic torque command value of the drive motor under different roll speed errors. Based on the electromagnetic torque command value Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). Based on the real-time response speed ω of different rolls in the rolling mill ei (k) and the response current i of the drive motor dqi (k) is used to observe the unknown disturbance terms of the d and q axes of the i-th drive motor. and

[0042] 2) The controller predicts the electromagnetic torque command value using a pre-set flux hyperlocal model. Stator flux linkage command value Unknown disturbance terms on the d and q axes of the i-th drive motor and To obtain the control signal of the i-th drive motor.

[0043] In step 2) of this embodiment, the preset flux hyperlocal model predictive controller is based on the electromagnetic torque command value. Stator flux linkage command value Unknown perturbation term estimated by discrete flux sliding mode observer and The function expression for obtaining the control signal of the drive motor is:

[0044]

[0045] In the above formula, g swi ξ represents the switching information controlling the i-th drive motor. i These are the weighting coefficients. Let be the stator flux linkage command value for the i-th drive motor. Let be the electromagnetic torque command value for the i-th drive motor. and These are the stator flux linkage observations of the i-th drive motor along the d and q axes at time k+1, respectively, and n p ψ is the number of pole pairs of the drive motor. ro For permanent magnet flux linkage, L o Let be the inductance parameters of the drive motor, and we have:

[0046]

[0047] In the above formula, χ di and χ qi For hypermodel parameters, χ di =χ qi =-R o / L o R o T represents the resistance parameter of the drive motor. s To control the period, ψ di (k) and ψ qi (k) represents the stator flux linkages of the i-th drive motor along the d and q axes at time k, respectively, and u di (k) and u qi (k) represents the d-axis and q-axis stator voltages of the i-th drive motor at time k. and Let ε be the unknown disturbance terms of the d and q axes of the i-th drive motor at time k. di and ε qi Let ε be the parameter of the hypermodel to be designed. di =ε qi =1. Formula (1) can solve the problem of the influence of external disturbances on the mill speed of different rolls in actual working conditions; Formula (2) can effectively compensate online for the speed error between different rolls of the mill caused by external disturbances.

[0048] In this embodiment, the step of designing a magnetic flux hyperlocal model prediction controller is included before step 2):

[0049] S1) The novel hyperlocal mathematical model of the magnetic flux linkage for the i-th driving permanent magnet motor is constructed as shown in the following equation:

[0050]

[0051] In the above formula, ψ di Let ψ be the stator flux linkage along the d-axis of the i-th drive motor. qi Let ω be the stator flux linkage on the q-axis of the i-th drive motor. ei Let i be the rotational speed of the i-th drive motor. di Let i be the d-axis current of the i-th drive motor. qi Let u be the q-axis current of the i-th drive motor. di Let u be the d-axis stator voltage of the i-th drive motor. qi Let u be the q-axis stator voltage of the i-th drive motor. di Let u be the d-axis stator voltage of the i-th drive motor. qi f is the q-axis stator voltage of the i-th drive motor. di For the mismatch term of the d-axis parameters of the i-th drive motor, f qi For the mismatch term of the q-axis parameter of the i-th drive motor, ψ ro For permanent magnet flux linkage, L o R is the inductance parameter of the drive motor. o Let Δψ be the resistance parameter of the drive motor. r χ represents the flux linkage variable after flux linkage parameter mismatch, and ΔL represents the inductance variable after inductance parameter mismatch. di and χ qi Let χ be the parameter of the hypermodel to be designed. di =χ qi =-R o / L o , ε di and ε qi The parameters of the supermodel to be designed are given; a flux linkage model considering different roll disturbances of the rolling mill is established by formula (3), which provides a basic model for subsequent operations;

[0052] S2) Discretize the novel hyperlocal mathematical model of the i-th driving permanent magnet motor flux obtained by the construction, and then analyze the unknown disturbance term observations. and Substituting the values, we obtain the functional expressions for the stator flux linkages of the i-th drive motor at time k+1, which are shown in equation (2).

[0053] S3) Based on the function expression of the stator flux linkage observation values ​​of the i-th drive motor at time k+1 shown in Equation (2), the function expression of the flux linkage hyperlocal model predictive controller is designed as shown in Equation (1).

[0054] In this embodiment, step 1) involves obtaining the electromagnetic torque command value of the drive motor under different roll speed errors. This is achieved through a speed controller based on synchronization error compensation. The speed controller includes a normal proportional-integral controller and an error-compensated proportional-integral controller. Furthermore, the speed controller based on synchronization error compensation acquires the electromagnetic torque command values ​​of the drive motor under different roll speed errors. This includes: coordinated control commands for the multi-motor drive system of the rolling mill. With the response speed ω of the rolls in the rolling mill ei The error of (k) is input to the proportional-integral controller under normal conditions to obtain the electromagnetic torque command value of different rolls in the rolling mill under normal conditions. The real-time response speed ω of different rolls in the rolling mill ei (k) and the average rotational speed ω between different rolls av The error of (k) is input to the error compensation proportional-integral controller to obtain the electromagnetic torque command value of different rolls in the rolling mill under the speed error. The electromagnetic torque command values ​​of different rolls in the rolling mill under normal conditions. Subtracting the speed error, the electromagnetic torque command value of different rolls in the rolling mill Obtain the electromagnetic torque command value of the drive motor under different roll speed errors. Right now:

[0055] In this embodiment, step 1) involves setting the electromagnetic torque command value. Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). This is achieved through the Maximum Torque-to-Current Ratio (MTPA) module, and the MTPA module transmits the electromagnetic torque command value. Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). The function expression is:

[0056]

[0057] In the above formula, ψ ro These are the flux linkage parameters of the rotor permanent magnet of the drive motor. n is the electromagnetic torque command value. p L represents the number of pole pairs of the drive motor. oThe inductance parameters of the drive motor can be obtained by formula (4) for the flux linkage command values ​​between different rolls of the rolling mill.

[0058] In this embodiment, the unknown disturbance terms of the d and q axes of the i-th drive motor are observed in step 1). and This is achieved through a discrete flux linkage sliding mode observer, and the functional expression of the discrete flux linkage sliding mode observer is:

[0059]

[0060] In the above formula, the subscript i represents the drive motor corresponding to any roll in the rolling mill. Let be the observed value of the stator flux linkage on the d-axis of the i-th drive motor at time k+1. Let be the observed value of the stator flux linkage on the q-axis of the i-th drive motor at time k+1. Let k be the d-axis stator flux linkage observation value of the i-th drive motor. Let ψ be the observed value of the stator flux linkage on the q-axis of the i-th drive motor at time k. di (k) represents the actual value of the stator flux linkage on the d-axis of the i-th drive motor at time k, ψ qi (k) represents the actual value of the q-axis stator flux linkage of the i-th drive motor at time k, u di (k) represents the d-axis stator voltage of the i-th drive motor at time k, u qi (k) represents the q-axis stator voltage of the i-th drive motor at time k. Let k be the observed value of the unknown disturbance term on the d-axis of the i-th drive motor at time k. Let ρ be the observed value of the unknown disturbance term of the i-th drive motor on the q-axis at time k. di ρ is the real-time adjustment parameter for the d-axis of the i-th drive motor. qi T is the real-time adjustment parameter for the q-axis of the i-th drive motor. s To control the period, ν is a small constant greater than zero, and χ di and χ qi Let χ be the parameter of the hypermodel to be designed. di =χ qi =-R o / L o , ε di and ε qi Let ε be the parameter of the hypermodel to be designed. di =ε qi =1,L o R is the inductance parameter of the drive motor. o The resistance parameters of the drive motor are given. An external disturbance observer for different rolls in the rolling mill was constructed using equation (5), which enables the observation of unknown disturbance terms.

[0061] In this embodiment, before step 1), the average rotational speed ω between different rolls of the rolling mill is calculated. av (k) Step: Detect the real-time response speed ω of different rolls in the rolling mill. e1 (k), ω e2 (k), ω ei (k), ω en (k), where ω ei (k) represents the real-time response speed of the i-th roll in the rolling mill; based on the real-time response speed ω of different rolls in the rolling mill e1 (k), ω e2 (k), ω ei (k), ω en (k), calculate the average rotational speed ω between different rolls of the rolling mill. av (k).

[0062] Figure 3 and Figure 4 A block diagram of the implementation of the multi-motor system flux hyperlocal model collaborative predictive controller for the i-th roll is given, where i can be any roll in the rolling mill. The multi-motor system flux hyperlocal model collaborative predictive controller 3 for the i-th roll mainly includes a speed controller 31 based on synchronization error compensation, a maximum torque-to-current ratio (MTPA) module 32, a flux hyperlocal model predictive controller 33, and a discrete flux sliding mode observer 34. The speed controller 31 based on synchronization error compensation mainly includes a normal-state proportional-integral (PI) controller 311 and an error-compensated PI controller 312. The normal-state PI controller 311 calculates the speed based on the deviation between the rolling mill roll command speed and the rolling mill roll response speed. To obtain the torque command value of the rolling mill rolls under normal conditions. The error compensation proportional-integral controller 312 calculates the error based on the deviation between the rolling mill roll response speed and the rolling mill roll average speed. To obtain the adjustment torque command value under the rolling mill roll speed error. The torque command value of the rolling mill rolls under normal conditions Adjustment torque command value under the error of rolling mill roll speed Deviation between The input is fed into the flux linkage hyperlocal model predictive controller 33. The maximum torque-to-current ratio (MTPA) module 32 is based on the torque command value of the mill rolls under normal conditions. Adjustment torque command value under the error of rolling mill roll speed Deviation between To obtain the stator flux linkage command value of the rolling mill rolls. and the stator flux linkage command value of the rolling mill rolls The input is fed into the flux linkage hyperlocal model predictive controller 33. The discrete flux linkage sliding mode observer 34 is used to observe the unknown disturbance term caused by parameter mismatch. And the observed values ​​of the unknown disturbance term The input is fed into the flux linkage hyperlocal model predictive controller 33. The specific implementation steps of the discrete flux linkage sliding mode observer 34 are as described in formula (5). The flux linkage hyperlocal model predictive controller 33 is based on the mill roll torque command value. Rolling mill roll stator magnetic flux command value Observations of unknown disturbance term To obtain the control signal for driving the rolling mill rolls, the specific implementation steps of the magnetic flux superlocal model predictive controller 33 are as described in formulas (1) to (3). Figure 5 Simulation results of the roll synchronization error of a six-roll mill using the multi-motor drive main transmission system flux superlocal cooperative predictive control method of this invention are presented. Figure 5 It can be seen that when there is no external disturbance, i.e., no parameter mismatch, the mill roll speed synchronization error is very small, essentially zero, after adopting the multi-motor drive main transmission system flux superlocal cooperative predictive control method of the present invention; when an unknown external disturbance occurs, i.e., parameter mismatch exists, the mill roll speed synchronization errors after adopting the multi-motor drive main transmission system flux superlocal cooperative predictive control method of the present invention are as follows:

[0063] ω e1 (k)-ω e2 (k)=0.005rad / s, ω e2 (k)-ω e3 (k) = 0.003 rad / s,

[0064] ω e3 (k)-ω e4 (k)=0.01rad / s, ω e4 (k)-ω e5 (k) = 0.013 rad / s,

[0065] ω e5 (k)-ω e6 (k) = 0.014 rad / s, ω e6 (k)-ω e1 (k) = 0.02 rad / s,

[0066] The maximum synchronization error of the rolling mill roll speed is 0.02 rad / s, which accounts for a certain percentage of the rolling mill roll command speed. The impact of unknown external disturbances on the precise coordinated control performance of the rolling mill rolls is very small after adopting the method described in this invention. Furthermore, the rolling mill roll speed achieves a rapid dynamic response under unknown disturbances of parameter mismatch, thereby improving the dynamic response performance and coordinated control accuracy of each roll in the rolling mill, eliminating the speed difference between rolling mill rolls, and preventing cracks and ripples on the surface of rolled steel.

[0067] In summary, the method in this embodiment is implemented through n multi-motor system flux hyperlocal model cooperative controllers. Each multi-motor system flux hyperlocal model cooperative controller includes a speed controller based on synchronization error compensation, a maximum torque-to-current ratio (MTPA) module, a flux hyperlocal model predictive controller, and a discrete flux sliding mode observer. The cooperative control commands for the rolling mill multi-motor drive system are then used. The actual speed ω of the roll ei (k) and the average rotational speed ω between different rolls av (k) Input to the speed controller based on synchronization error compensation to obtain the electromagnetic torque command value of the drive motor under different roll speed errors. Electromagnetic torque command value The input is fed into the Maximum Torque-to-Current Ratio (MTPA) module to obtain the stator flux linkage command value for the rolling mill rolls. Electromagnetic torque command value Stator flux linkage command value Unknown perturbation term estimated by discrete flux sliding mode observer The input is fed into the flux linkage hyperlocal model predictive controller to obtain the control signal for the drive motor, thereby achieving high-precision robust cooperative control of the multi-motor drive main transmission system of the rolling mill. The implementation of this invention can significantly improve the anti-interference capability and cooperative control performance of the multi-motor drive main transmission system of the rolling mill, effectively enhance the synchronous operation performance of different rolls in the rolling mill, eliminate the influence of unknown disturbances on the precise cooperative control of the rolling mill rolls, and ensure the quality and service life of the rolled steel. It should be noted that the various controllers mentioned above are actually the main body executing a specific set of control functions. Given that the above control functions are already disclosed, they can be implemented using a single physical controller, or the control functions of some or all controllers can be combined to implement the control using multiple independent physical controllers.

[0068] Furthermore, corresponding to the method described above in this embodiment, this embodiment also provides a collaborative predictive control system for a multi-motor driven main drive system of a rolling mill, including: a rolling mill roll speed detection unit, used to collect the actual speed ω of the rolls. ei (k) and the average rotational speed ω between different rolls av(k); Multi-motor system flux hyperlocal model cooperative controller, used to execute the steps of the aforementioned cooperative predictive control method for the multi-motor drive main transmission system of the rolling mill, and output the obtained control signals of the drive motors to the control signal input terminal of each drive motor in the multi-motor drive main transmission system of the rolling mill; the output terminal of the rolling mill roll speed detection unit is connected to the input terminal of the multi-motor system flux hyperlocal model cooperative controller.

[0069] In addition, corresponding to the method described in this embodiment, this embodiment also provides a cooperative predictive control system for a multi-motor drive main transmission system of a rolling mill, including a microprocessor and a memory connected to each other. The microprocessor is programmed or configured to execute the steps of the cooperative predictive control method for the multi-motor drive main transmission system of the rolling mill described above.

[0070] In addition, corresponding to the method described in this embodiment, this embodiment also provides a computer-readable storage medium storing a computer program for execution by a computer device to implement the aforementioned cooperative predictive control method for the multi-motor drive main transmission system of a rolling mill.

[0071] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0072] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A cooperative predictive control method for a multi-motor driven main drive system of a rolling mill, characterized in that, include: 1) Based on the coordinated control instructions of the multi-motor drive system of the rolling mill Actual speed of the rolls and the average rotational speed between different rolls To obtain the electromagnetic torque command value of the drive motor under different roll speed errors. According to the electromagnetic torque command value Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). Based on the real-time response speed of different rolls in the rolling mill With the response current of the drive motor To observe the first i One drive motor d, q Axis unknown disturbance term and ; 2) The controller predicts the electromagnetic torque command value using a pre-set flux hyperlocal model. Stator flux linkage command value , No. i One drive motor d, q Axis unknown disturbance term and To obtain the i Control signals for each drive motor; In step 2), the preset flux hyperlocal model predictive controller predicts the electromagnetic torque command value. Stator flux linkage command value Unknown perturbation terms estimated by discrete flux sliding mode observer and The function expression for obtaining the control signal of the drive motor is: ，（1） In the above formula, Indicates control of the first i Switching information for each drive motor. These are the weighting coefficients. For the first i Stator flux linkage command value for each drive motor For the first i The electromagnetic torque command value of each drive motor. and They are respectively k +1 moment i One drive motor d, q Observations of stator flux linkage This represents the number of pole pairs of the drive motor. It is a permanent magnet flux chain. Let be the inductance parameters of the drive motor, and we have: ，（2） In the above formula, and For hypermodel parameters, , These are the resistance parameters of the drive motor. To control the cycle, and They are respectively k Time of the first i One drive motor d, q Shaft stator flux linkage and They are respectively k Time of the first i One drive motor d, q Shaft stator voltage, and They are respectively k The first moment i One drive motor d, q Unknown disturbance term along axis and The parameters of the hypermodel to be designed are... .

2. The cooperative predictive control method for a multi-motor driven main drive system of a rolling mill according to claim 1, characterized in that, Step 2) is preceded by the step of designing a flux hyperlocal model predictive controller: S1) Construct the first i The mathematical model of a novel flux hyperlocality driving permanent magnet motor is shown in the following equation: ，（3） In the above formula, For the first i One drive motor d Shaft stator flux linkage, For the first i One drive motor q Shaft stator flux linkage For the first i The speed of each drive motor For the first i One drive motor shaft current, For the first i One drive motor shaft current, For the first i One drive motor Shaft stator voltage, For the first i One drive motor Shaft stator voltage, For the first i One drive motor Shaft stator voltage, For the first i One drive motor Shaft stator voltage, For the first i One drive motor Shaft parameter mismatch, For the first i One drive motor Shaft parameter mismatch, It is a permanent magnet flux linkage. These are the inductance parameters of the drive motor. These are the resistance parameters of the drive motor. This refers to the flux linkage variable after flux linkage parameter mismatch. This refers to the inductance variable after inductance parameter mismatch; and The parameters of the hypermodel to be designed are... , and The parameters of the hypermodel to be designed; S2) The constructed first i A novel hyperlocal mathematical model of flux linkage for a driving permanent magnet motor is discretized, and the observed values ​​of the unknown disturbance term are used. and Substitute and get k +1 moment i One drive motor d, q The functional expression for the observed values ​​of the stator flux linkage is shown in equation (2); S3) as shown in equation (2) k +1 moment i One drive motor d, q Based on the functional expression of the stator flux linkage observation, the functional expression of the flux linkage hyperlocal model predictive controller is designed as shown in equation (1).

3. The cooperative predictive control method for the multi-motor drive main transmission system of a rolling mill according to claim 2, characterized in that, In step 1), the electromagnetic torque command value of the drive motor under different roll speed errors is obtained. This is achieved through a speed controller based on synchronization error compensation. The speed controller includes a normal proportional-integral controller and an error-compensated proportional-integral controller. Furthermore, the speed controller based on synchronization error compensation acquires the electromagnetic torque command values ​​of the drive motor under different roll speed errors. This includes: coordinated control commands for the multi-motor drive system of the rolling mill. Response speed of the rolls in the rolling mill The error is input to the proportional-integral controller under normal conditions to obtain the electromagnetic torque command value of different rolls in the rolling mill under normal conditions. The real-time response speed of different rolls in the rolling mill. Average rotational speed between different rolls The error is input to the error compensation proportional-integral controller to obtain the electromagnetic torque command value of different rolls in the rolling mill under the speed error. ; The electromagnetic torque command values ​​of different rolls in the rolling mill under normal conditions Subtracting the speed error, the electromagnetic torque command value of different rolls in the rolling mill Obtain the electromagnetic torque command value of the drive motor under different roll speed errors. .

4. The cooperative predictive control method for a multi-motor driven main drive system of a rolling mill according to claim 3, characterized in that, In step 1), the electromagnetic torque command value is... Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). This is achieved through the Maximum Torque-to-Current Ratio (MTPA) module, and the MTPA module transmits the electromagnetic torque command value. Stator flux command value is obtained based on maximum torque-to-current ratio (MTPA). The function expression is: ，（4） In the above formula, These are the flux linkage parameters of the rotor permanent magnet of the drive motor. This is the electromagnetic torque command value. This represents the number of pole pairs of the drive motor. These are the inductance parameters of the drive motor.

5. The cooperative predictive control method for a multi-motor driven main drive system of a rolling mill according to claim 4, characterized in that, In step 1), the observation of the first i One drive motor d, q Axis unknown disturbance term and This is achieved through a discrete flux linkage sliding mode observer, and the functional expression of the discrete flux linkage sliding mode observer is: ，（5） In the above formula, the subscript i This indicates the drive motor corresponding to any roll in the rolling mill. for k +1 moment i One drive motor d Observations of stator flux linkage for k +1 moment i One drive motor q Observations of stator flux linkage for k Time of the first i One drive motor d Observations of stator flux linkage for k Time of the first i One drive motor q Observations of stator flux linkage for k Time of the first i One drive motor d Actual value of stator flux linkage for k Time of the first i One drive motor q Actual value of stator flux linkage for k Time of the first i One drive motor d Shaft stator voltage, for k Time of the first i One drive motor q Shaft stator voltage, for k Time of the first i One drive motor d Observations of unknown disturbance terms along the axis for k Time of the first i One drive motor q Observations of unknown disturbance terms along the axis For the first i One drive motor d Real-time adjustment parameters of the shaft For the first i One drive motor q Real-time adjustment parameters of the shaft To control the cycle, It is a small constant greater than zero. and The parameters of the hypermodel to be designed are... , and The parameters of the hypermodel to be designed are... , These are the inductance parameters of the drive motor. These are the resistance parameters of the drive motor.

6. The cooperative predictive control method for a multi-motor driven main drive system of a rolling mill according to claim 5, characterized in that, Step 1) also includes calculating the average rotational speed between different rolls of the rolling mill. Steps: Detect the real-time response speed of different rolls in the rolling mill. , , , ,in Indicates the first in the rolling mill i The real-time response speed of each roll; based on the real-time response speed of different rolls in the rolling mill. , , , Calculate the average rotational speed between different rolls of the rolling mill. .

7. A cooperative predictive control system for a multi-motor driven main drive system of a rolling mill, characterized in that, include: The rolling mill roll speed detection unit is used to collect the actual speed of the rolls. and the average rotational speed between different rolls The multi-motor system flux linkage hyperlocal model cooperative controller is used to execute the steps of the cooperative predictive control method of the multi-motor drive main transmission system of the rolling mill according to any one of claims 1 to 6, and outputs the obtained control signals of the drive motors to the control signal input terminal of each drive motor in the multi-motor drive main transmission system of the rolling mill respectively; the output terminal of the rolling mill roll speed detection unit is connected to the input terminal of the multi-motor system flux linkage hyperlocal model cooperative controller.

8. A cooperative predictive control system for a multi-motor drive main transmission system of a rolling mill, comprising a microprocessor and a memory interconnected, characterized in that, The microprocessor is programmed or configured to perform the steps of the cooperative predictive control method for the multi-motor drive main drive system of a rolling mill as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program for execution by a computer device to implement the cooperative predictive control method for the multi-motor drive main transmission system of a rolling mill as described in any one of claims 1 to 6.

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