Genetic algorithm approach for controlling nonlinear systems

Author

Patil, Utkarsh ; Katkol, Pronita ; Havagondi, Menka ; Patil, Ajay

Author_Institution

Dept. of Electr. Eng., Walchand Coll. of Eng., Sangli, India

fYear

2014

Firstpage

944

Lastpage

949

Abstract

In all the industrial applications nonlinear systems are very common. For controlling such systems various controllers are used from decades, such as manual controller, P, PI, PID, and fuzzy controllers. In recent decade new family of intelligent controllers has been evolved because of vary complicated systems and due to requirement of accuracy in the process. The paper consists of simple fuzzy controller designed for nonlinear system and optimized fuzzy controller in which genetic algorithm is used to optimize the fuzzy rules. Here in this paper the CSTR model is considered to design a fuzzy controller. At the end, simulation results are given to show the effectiveness of system with optimized fuzzy controller.

Keywords

chemical reactors; control system synthesis; fuzzy control; genetic algorithms; intelligent control; nonlinear control systems; CSTR model; continuously stirred tank reactor; fuzzy controller design; fuzzy rules optimization; genetic algorithm approach; intelligent controllers; nonlinear control systems; Chemical reactors; Control systems; Delay effects; Genetic algorithms; Inductors; Mathematical model; Nonlinear systems; Fuzzy control; Genetic algorithm; Takagi-Sugeno (T-S) fuzzy approach; nonlinear systems; time-delay systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on

Print_ISBN

978-1-4799-2395-3

Type

conf

DOI

10.1109/ICCPCT.2014.7054972

Filename

7054972