A Global Sliding Mode Fuzzy Control Method for Micro Gyroscope Inversion Based on Neural Network

Abstract

The invention discloses a neural network-based micro-gyroscope inversion global sliding mode fuzzy control method, which is based on the neural network inversion global sliding mode fuzzy control system consisting of an inversion global sliding mode controller and a neural network dynamic characteristic estimator and a fuzzy uncertainty estimator. The global sliding mode control can overcome the shortcomings of the arrival mode not being robust in the traditional sliding mode control, speed up the system response, and make the system robust in the whole process of response. The method makes the Lyapunov function of the system and the design process of the controller systematized and structured through reverse design during the inverse control. Using fuzzy control to approximate switching function items, the switching items of sliding mode control are transformed into continuous fuzzy control output, which weakens the chattering phenomenon in sliding mode control and has strong adaptive tracking ability. Therefore, the transient characteristics and robustness of the sliding mode control system are improved, the unknown dynamic characteristics of the micro gyroscope are estimated and chattering in the sliding mode variable structure control is reduced.

Description

technical field [0001] The invention relates to the technical field of micro-gyroscope control, in particular to a neural network-based micro-gyroscope inversion global sliding mode fuzzy control method. 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 ...

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Problems solved by technology

However, the robustness of adaptive control to external disturbances is very low, and it is easy to make the system unstable.

[0004] This shows that above-mentioned existing gyroscope obviously still has inconvenience and defect in use, and urgently needs to be further improved

In order to solve the problems existing in the use of existing gyroscopes, relevant manufacturers have tried their best to find a solution, but no suitable design has been developed for a long time

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