Title :
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
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;
Conference_Titel :
Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on
Print_ISBN :
978-1-4799-2395-3
DOI :
10.1109/ICCPCT.2014.7054972
