Chaotic fuzzy control method for permanent magnet synchronous motor based on series-parallel estimation model

Abstract

Provided is a permanent magnet synchronous motor chaotic fuzzy adaptive control method based on a dynamic surface sliding model. The method includes: establishing a dynamic model of a permanent magnet synchronous motor chaotic system, and initializing the system state, sampling time, and control parameters; defining a sliding model surface, introducing a virtual controlled variable in each step of design with the combination of the dynamic surface control technology, and enabling the virtual controlled variables to pass through a first-order low-pass filter in sequence to avoid the problem of complexity explosion brought by the conventional inversion control method; compensating an unknown non-linear uncertain item in a mechanical arm system by employing a self-learning and adaptive capability controlled by a fuzzy neural network; and based on a series-parallel estimation model, defining a variable predicted value and designing a related change rule to improve the robustness and stable-state control precision of a control system. According to the fuzzy adaptive control method based on the dynamic surface sliding model, the control performance of the permanent magnet synchronous motor chaotic system can be improved, and accurate and rapid tracking of the system is realized.

Description

technical field [0001] The invention relates to a chaotic fuzzy control method of a permanent magnet synchronous motor based on a series-parallel estimation model, in particular to a control method of a permanent magnet synchronous motor chaotic system with unknown nonlinear uncertain items. Background technique [0002] Permanent magnet synchronous motor is a typical multivariable, strongly coupled high-order nonlinear system, which has been widely used in high-performance systems such as robots, numerical control machine tools, aerospace vehicles, and servo turntable control. However, research in recent years has shown that under some specific parameters and working conditions, permanent magnet synchronous motors will appear complex irregular motions, that is, chaotic behavior. The existence of chaotic behavior will generate irregular current noise, which will not only affect the stability and safety of the system operation, but also cause the system to collapse in severe ...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problems of unknown nonlinear uncertain items in the existing permanent magnet synchronous motor chaotic system, the complexity explosion caused by the inversion method and the poor robustness of the system, the present invention proposes a permanent magnet synchronous motor based on a series-parallel estimation model The chaotic fuzzy control method, combined with sliding mode and dynamic surface control technology, avoids the "complexity explosion" problem caused by the traditional inversion control method. Using fuzzy adaptive control technology and series-parallel estimation model, by defining the prediction error, state The variable prediction value and its change law, combined with the Lyapunov theoretical design method, can effectively reduce the approximation error of the neural network or fuzzy system. On this basis, the parameter adaptive law and control law are designed to realize the fast and stable tracking of the system.

Images