Robust Adaptive Control for Nonlinear Uncertain Systems Using Type-2 Fuzzy Neural Network System | Zendy

ChingHung Lee | Zendy; Yu-Ching Lin | Zendy

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Robust Adaptive Control for Nonlinear Uncertain Systems Using Type-2 Fuzzy Neural Network System

Author(s) -

ChingHung Lee,

Yu-Ching Lin

Publication year - 2011

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2011/604391

Subject(s) - control theory (sociology) , scheme (mathematics) , artificial neural network , controller (irrigation) , convergence (economics) , nonlinear system , computer science , adaptive control , type (biology) , fuzzy logic , adaptive neuro fuzzy inference system , neuro fuzzy , fuzzy control system , control engineering , control (management) , artificial intelligence , engineering , mathematics , mathematical analysis , ecology , physics , quantum mechanics , agronomy , economics , biology , economic growth

This paper proposes a novel intelligent control scheme using type-2 fuzzy neural network (type-2 FNN) system. The control scheme is developed using a type-2 FNN controller and an adaptive compensator. The type-2 FNN combines the type-2 fuzzy logic system (FLS), neural network, and its learning algorithm using the optimal learning algorithm. The properties of type-1 FNN system parallel computation scheme and parameter convergence are easily extended to type-2 FNN systems. In addition, a robust adaptive control scheme which combines the adaptive type-2 FNN controller and compensated controller is proposed for nonlinear uncertain systems. Simulation results are presented to illustrate the effectiveness of our approach

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