Super twisted sliding mode control system design method with microgyroscope double-feedback fuzzy neural network

Abstract

The invention discloses a super twisted sliding mode control system design method with a microgyroscope double-feedback fuzzy neural network. The control system comprises a reference model, a slidingmode surface, an adaptive law, a double-feedback fuzzy neural network approximator, a super twisted fuzzy sliding mode controller and a micro Gyro system. In order to solve problems of the unknown model of the actual microgyroscope system and the parameter uncertainty, the invention puts forward a double-feedback-fuzzy-neural-network-based adaptive super twisted sliding mode control method of a microgyroscope system. Compared with the traditional neural network control, the designed double closed-loop fuzzy neural network has the advantage of full adjustment; the initial values of the centervector and the base width can be set randomly; and the center vector, the base width value and the weight of the neural network can be adjusted to be optimal values adaptively according to differentinputs based on the designed adaptive algorithm. The adaptive algorithm is derived from the Lyapunov stability theory. Because of adding of the signal regression loop, the dynamic double feedback neural network can store much information and the approximation precision of the unknown model of the microgyroscope system is improved. With combination of the superiority of the high-order super-twistedalgorithm, the control input chattering of the system can be suppressed effectively; the system converges in limited time is ensured; and the reference trajectory is tracked quickly and accurately, so that the control system performance is improved. The experiment verification is carried out by using the algorithm superiority of the MATLAB.

Description

technical field [0001] The invention relates to a self-adaptive super-twist sliding mode control method for a micro-gyro system based on a double-feedback fuzzy neural network, and belongs to the technical field of micro-gyroscope control. Background technique [0002] Gyroscopes are the basic measurement elements of inertial navigation and inertial guidance systems. Because of its huge advantages in cost, volume, and structure, micro-gyroscopes are widely used in civil and military fields such as navigation, aerospace, aviation, and oil field survey and development, and land vehicle navigation and positioning. Because of the influence of errors and temperature in the design and manufacture, it will cause the difference between the characteristics of the original and the design, which will lead to the reduction of the sensitivity and accuracy of the gyroscope system. The main problem of the micro gyroscope control is to compensate the manufacturing error and measure the angu...

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Problems solved by technology

[0005] In order to improve the performance of the micro-gyroscope system, improve its robustness, and solve the existing defects of the micro-gyroscope and the shortcomings of traditional control methods, the present invention proposes a design method for the micro-gyroscope double-feedback fuzzy neural network super-distortion sliding mode control system, making full use of Advantages of dual-feedback fuzzy neural network control, adaptive control and super-twist sliding mode control

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