Double inverted pendulum decoupling control by adaptive terminal sliding-mode recurrent fuzzy neural network

Authors:
Yi-Jen Mon;Chih-Min Lin
Affiliations:
Department of Computer Science and Information Engineering, Taoyuan Innovation Institute of Technology, Chung-Li, Taoyuan, Taiwan, R.O.C;Department of Electrical Engineering, Yuan Ze University, Chung-Li, Taoyuan, Taiwan, R.O.C
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2014

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Abstract

An adaptive terminal sliding-mode recurrent fuzzy neural network ATSRFNN control system is developed to control a coupled double inverted pendulum system. The proposed ATSRFNN control system is composed of a recurrent fuzzy neural network RFNN controller and an adaptive terminal sliding ATS controller. The RFNN controller is designed to mimic an ideal controller, and the ATS controller is designed to cope with the approximation error and external disturbance. The simulation results show the proposed ATSRFNN control system can achieve better control performance and robustness in comparison with a hierarchical fuzzy sliding-mode control system.