Recurrent TS Fuzzy Neural Network and Its Application on Controlling Nonlinear Time-Delay Systems

This paper proposes a TS recurrent fuzzy neural network (RFNN) and a robust RFNN control of uncertain nonlinear time-delay systems. First, the TS-RFNN is proposed to learn complex functions with delays. Next, the robust adaptive TS-RFNN control is developed for time-delay nonlinear systems. The advantages of the proposed controller includes: i) asymptotic stability independent on the delay; ii) more simple and legible gain design; and iii) simpler structure of FNN (fewer fuzzy rules). Simulation results demonstrate the validity of the proposed control scheme

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