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Two-degree-of-freedom control using recurrent fuzzy neural networks for a class of nonlinear discrete-time time-delay systems

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2 Author(s)
Ching-Chih Tsai ; Dept. of Electr. Eng., Nat. Chung-Hsing Univ., Taichung, Taiwan ; Ya-Ling Chang

This paper presents a novel two-degrees-of-freedom control for a class of nonlinear discrete-time time-delay systems. The controller combines a TSK-type recurrent fuzzy neural network (TRFNN) adaptive inverse model feedforward controller with a stochastic adaptive model reference predictive controller (SAMRPC). The former is used to provide command-feedforward control and to improve transient performance, while the SAMRPC controller is employed to eliminate any error caused by disturbances or uncertainties. Numerical simulations for controlling a highly nonlinear process reveal disturbance rejection and set-point tracking performance of the proposed control method. The results clearly indicate effectiveness and merit of the proposed method.

Published in:

System Science and Engineering (ICSSE), 2012 International Conference on

Date of Conference:

June 30 2012-July 2 2012