Research on modeling and simulation of sliding mode control based on RBF neural network

Zixuan Yang; Xin Li

doi:10.1117/12.2634929

25 April 2022 Research on modeling and simulation of sliding mode control based on RBF neural network

Zixuan Yang, Xin Li

Proceedings Volume 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022); 122445I (2022) https://doi.org/10.1117/12.2634929
Event: 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 2022, Guilin, China

Abstract

In essence, sliding mode structure control is a particular nonlinear control, its speciality is most reflected in its dynamics. It can change dynamically according to a certain state of the system, and make the system change according to the condition track of the predetermined sliding mode in the change process. This paper firstly expounds the basic theory of sliding mode variable structure control from the definition of sliding mode composed and the condition of sliding mode variable structure control satisfied, then explains the working principle of RBFNN, then gives the modeling and simulation example of RBF network Matlab based on approximation algorithm, and finally summarizes the application of RBFNN in sliding mode structure control.

Citation Download Citation

Zixuan Yang and Xin Li "Research on modeling and simulation of sliding mode control based on RBF neural network", Proc. SPIE 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 122445I (25 April 2022); https://doi.org/10.1117/12.2634929

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