Minimum variance-based nonlinear model prediction controller design method for permanent magnet servo system

A nonlinear model and predictive controller technology, applied in the control of electromechanical brakes, control systems, and generators, etc., can solve problems such as difficulty in achieving high-performance motor control, large actual deviation, and failure to achieve optimal control.

Inactive Publication Date: 2016-08-17
SHANDONG UNIV OF TECH
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Problems solved by technology

Model predictive control was originally proposed for linear systems. However, since PMSM is a very typical nonlinear, multivariable, and strongly coupled model system, when the model parameters are inaccurate, the output prediction of the linear model is more accurate than the actual deviation. Large, the effect of optimal control cannot be achieved, and it is difficult to achieve high-performance control of the motor, so it can no longer be simply processed by the linear model predictive control algorithm

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  • Minimum variance-based nonlinear model prediction controller design method for permanent magnet servo system
  • Minimum variance-based nonlinear model prediction controller design method for permanent magnet servo system
  • Minimum variance-based nonlinear model prediction controller design method for permanent magnet servo system

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Embodiment Construction

[0068] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0069] figure 1 For the general block diagram of the servo control system required by the present invention, as figure 1 As shown, the rotor position signal θ of the PMSM servo system is obtained through a photoelectric encoder.

[0070] In the first step, the three-phase current i of the PMSM stator is obtained by sampling the current sensor a i b and i c , and then transformed into the d-axis current i in the two-phase rotating coordinate system through Clark transformation (3s / 2s) and Park transformation (2s / 2r) d and q-axis current i q .

[0071] According to the voltage equation (30), flux equation (31), torque equation (32) and motion equation (33) of the PMSM system in the two-phase rotating dq coordinate system, its differential equation (34) is obtained.

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Abstract

The invention discloses a minimum variance-based nonlinear model prediction controller (NMPC) design for a permanent magnet servo system, and belongs to the technical field of high-performance servo control systems. The method comprises the steps as follows: firstly, a nonlinear mathematic model of a PMSM is built under a dq coordinate system; secondly, a cost function of the prediction control rate of the PMSM is selected on the basis of the model according to the minimum variance prediction control theory; and the selected cost function is minimized to search for the optimal control rate in a receding horizon, so that output of the system within prediction time can track a given reference value to reach the prediction control target. Through a receding horizon control strategy of model prediction control (MPC), adverse effects caused by various system model parameter changes and uncertain random disturbance can be processed online by the control system; and the disturbance resistance of the control system is strengthened. Through an experiment, high-rotating speed tracking performance and good robustness of the method in an actual control system are verified.

Description

technical field [0001] The invention relates to a design method of a nonlinear model predictive controller of a permanent magnet servo system based on minimum variance, and belongs to the technical field of high-performance servo control systems. Background technique [0002] At present, the AC permanent magnet servo system is widely used in wind power generation, industrial robots, new energy vehicles and other fields. High-performance control occasions require PMSM to have a strong speed tracking ability, and to ensure the strong performance of the system under system parameter changes and load disturbances. robustness. However, the strong coupling and nonlinearity of the PMSM system, the uncertainty of model parameters, external disturbances and end effects make it difficult for traditional control methods and conventional linear control methods to effectively control it. [0003] In recent years, in order to improve the speed tracking and anti-disturbance characteristic...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02P21/00
CPCH02P21/00H02P21/0021
Inventor 季画张厚升邢雪宁王红梅
Owner SHANDONG UNIV OF TECH
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