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
Note: [] Corresponding author. Yi-Jen Mon, Department of Computer Science and Information Engineering, Taoyuan Innovation Institute of Technology, Chung-Li, Taoyuan, 320 Taiwan, R.O.C. Tel.: +886 3 4361070 6937; Fax: +886 4361070 6999; E-mail: monbuy@tiit.edu.tw
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.
