Self-adaption fuzzy neural compensating nonsingular terminal sliding mode control method of micro gyroscope

Abstract

The invention discloses a self-adaption fuzzy neural compensating nonsingular terminal sliding mode control method of a micro gyroscope. The method mainly involves a nonsingular terminal sliding mode controller and a fuzzy neural network compensating controller; the designed nonsingular terminal sliding mode enables that a system can reach a sliding mode surface and a balance point within a limited time from any initial state, and therefore, the convergence rate and steady stacking precision of the system are improved; meanwhile, the fuzzy neural network compensates the parametric modeling error of the micro gyroscope and outside disturbance effect on line, in order to improve the tracking performance; the fuzzy neural network is practiced on line, the self-adaption learning algorithm of weight of the fuzzy neural is on the basis of the lyapunov stability theorem, which ensures the tracking performance and the stability of the whole control system. The simulation result shows that the method is able to improve the problem of trace tracking of the micro gyroscope and can also effectively inhibit the parameter uncertainty and the influence from the outside disturbance, and as a result, the robust tracking can be realized.

Description

technical field [0001] The invention relates to a self-adaptive fuzzy neural compensation non-singular terminal sliding mode control method of a micro gyroscope, which belongs to the technical field of micro gyroscope control. Background technique [0002] Micro gyroscopes are the basic measurement components of inertial navigation and inertial guidance systems. Because of their huge advantages in size and cost, micro gyroscopes are widely used in aviation, aerospace, automotive, biomedical, military and consumer electronics. 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. In addition, the micro gyroscope itself is a multi-input multi-output system and the system parameters are uncertain and susceptible to the influence of the external environment. Compensating manufacturing e...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that when the state trajectory reaches the sliding surface, it is difficult to slide strictly along the sliding surface toward the equilibrium point, but crosses back and forth on both sides of the sliding surface, resulting in vibration

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