Dynamic PID global sliding mode control method of micro gyroscope neural network

Abstract

The invention discloses a dynamic PID global sliding mode control method of a micro gyroscope neural network. A neural network dynamic PID global sliding mode control system comprises a dynamic PID global sliding mode controller and a neural network uncertainty estimator. Global sliding mode control can overcome the disadvantage that the mode state in the traditional sliding mode control does not have robustness, quickens the system response, and ensures that the system has robustness during the whole response process. According to the method, an integral item is introduced in the design of sliding mode surface, so as to restrain steady state error and improve robustness, moreover, dynamic sliding mode control can reduce buffeting phenomenon, so that the combination of PID global sliding mode and dynamic sliding mode can develop respective advantages at the same time, improve the transient performance and the robustness of the sliding mode control system and reduce the frequency of buffeting during sliding mode variable structure control.

Description

technical field [0001] The invention relates to the technical field of control of micro-gyroscopes, in particular to a dynamic PID global sliding mode control method of neural network of micro-gyroscopes. Background technique [0002] Micro gyroscope is the basic measurement element of inertial navigation and inertial guidance system. Because of its huge advantages in size and cost, microgyroscopes are widely used in aviation, aerospace, automotive, biomedical, military and consumer electronics fields. However, due to the existence of errors in design and manufacture and temperature perturbation, the difference between the original characteristics and the design will be caused, which will reduce the performance of the micro-gyroscope system. The micro-gyroscope itself belongs to the multiple-input multiple-output system, and the system parameters are uncertain and easily affected by the external environment. Compensating manufacturing errors and measuring angular velocity ...

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Problems solved by technology

[0005] The purpose of the present invention is to overcome the defects in the existing micro-gyroscope control method, especially to improve the micro-gyroscope system in the presence of various disturbances such as model uncertainty, parameter perturbation and external noise, and eliminate system chattering. Without affecting the tracking performance of the ideal trajectory and the robustness of the whole system, a dynamic PID global sliding mode control method of the micro-gyroscope neural network is provided

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