Overall situation sliding mode control method of micro gyroscope adaptive neural network

Abstract

The invention discloses an overall situation sliding mode control method of a micro gyroscope adaptive neural network. Firstly, a novel adaptive identification method is designed on the basis of an overall situation sliding mode controller and the angular speed of a micro gyroscope and the estimated values of other system parameters are updated online in real time; secondly, the switch gain in a sliding mode control switching item is dynamically adjusted through the adaptive neural network system output to approach to the upper bound of the nondeterminacy of the system and the external disturbance, the switching item of the sliding mode control is converted to continuous neural network output, the buffeting phenomenon in sliding mode control is weakened, and the high adaptive trace ability is achieved. The adaptive algorithm is designed based on the Lyapunov method, the ideal model on the micro gyroscope track and the overall situation asymptotic stability of the system are guaranteed, and the estimated values of an identifier can approach to the respective true value in an asymptotic convergence mode.

Description

technical field [0001] The invention relates to a micro-gyroscope adaptive neural network global sliding mode control method, which belongs to the technical field of micro-gyroscope control. Background technique [0002] Micro gyroscopes are fundamental measurement elements in inertial navigation and inertial guidance systems. Because of its huge advantages in size and cost, micro gyroscopes are widely used in aviation, aerospace, automotive, biomedical, military and consumer electronics fields. However, due to the existence of errors in design and manufacturing and temperature disturbances, there will be differences between the characteristics of the original and the design, which will reduce the performance of the micro gyroscope system. The micro gyroscope itself belongs to the multi-input multi-output system and the system parameters are uncertain and susceptible to the influence of the external environment. Compensating manufacturing errors and measuring angular veloc...

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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 entire system, a global sliding mode control method for the adaptive neural network of the micro-gyroscope is provided

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