Permanent magnet synchronous motor (PMSM) servo system control method based on fuzzy and active disturbance rejection control

Abstract

The invention relates to a PMSM servo system control method based on fuzzy and active disturbance rejection control. A position signal is given by a differential tracker to arrange a transition process so that the contradiction between rapidness and overshoot of a system is solved, and uncertainty, friction torques and external disturbance due to modeling errors of the system are observed via an expansion state observer; according to the error between the differentials generated by the differential tracker and state variation generated by the expansion state observer, a fuzzy inference rule is obtained with application of experimental experience of technical staff, so that a fuzzy rule control table of an error proportion coefficient, a differential coefficient and an integration coefficient is established; accurate control amount is obtained after de-fuzzification, so that parameter self-adaptive adjustment of a nonlinear error feedback control law is realized; and compensation amounts of the nonlinear error feedback control law and the expansion state observer to the total disturbance forms the control amount, thereby realizing optimal control for an controlled object. The method of the invention improves both tracking precision and disturbance rejection capability of the system.

Description

[0001] technical field

[0002] The invention relates to a control method of a permanent magnet synchronous motor (PMSM) servo system based on fuzzy self-disturbance rejection, and belongs to the technical field of high-precision servo control systems. Background technique

[0003] With the improvement of the control precision of the servo system, the system disturbance becomes an important factor affecting the precision of the servo control system. Disturbances often come from uncertain factors neglected in the modeling process, friction torque during system operation, sudden load changes, and parameter changes. The existence of these factors makes the performance of the closed-loop system worse or even unstable. In addition, under different operating conditions of the system, the control parameters of the system controller are different, which need to be manually adjusted in sections, and it is difficult to achieve precise adjustment in practice to achieve the best control p...

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