Neuro Genetic Fuzzy System For Gain Scheduling Adaptive Control Design

Author

Serra, Ginalber L O ; Bottura, Celso P.

Author_Institution

Intelligent Syst. & Control Lab., UNICAMP

Volume

1

fYear

2006

fDate

16-18 Oct. 2006

Firstpage

942

Lastpage

947

Abstract

This paper proposes a gain scheduling adaptive control scheme based on fuzzy systems, neural networks and genetic algorithms: an optimal fuzzy PI controller is developed, by a genetic algorithm, according to some design specifications, and a neural network is designed to learn and tune online the fuzzy controller parameters at different operating points from ones used in the learning process. Simulation results are shown to demonstrate the efficiency of the proposed structure for DC servomotor adaptive speed control design

Keywords

PI control; adaptive control; control system synthesis; fuzzy control; fuzzy systems; genetic algorithms; neurocontrollers; optimal control; DC servomotor adaptive speed control design; gain scheduling; genetic algorithm; learning process; neural network; neuro genetic fuzzy system; optimal fuzzy PI controller; Adaptive control; Adaptive scheduling; Algorithm design and analysis; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Neural networks; Optimal control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on

Conference_Location

Jinan

Print_ISBN

0-7695-2528-8

Type

conf

DOI

10.1109/ISDA.2006.203

Filename

4021566