PID control based on modified particle swarm optimization for nonlinear process

Author

Taeib, Adel ; Ltaief, Ali ; Chaari, Abdelkader

Author_Institution

Univ. of Tunis, Tunis, Tunisia

fYear

2013

fDate

22-24 June 2013

Firstpage

1

Lastpage

5

Abstract

In this paper, a novel design method for determining the optimal proportional-integral-derivative (PID) controller parameters for Takagi-Sugeno (T-S) fuzzy model using a Modified Particle Swarm Optimization (MPSO) with random inertia weight algorithm is presented. In this scheme, an inertia weight of PSO is randomly adjusted during searching process to overcome the difficulties of the method of selecting inertia weight and to improve the performance of the standard PSO. The performance of the self-tuning PID controller based on MPSO has been tested on academic nonlinear system.

Keywords

control system synthesis; fuzzy control; nonlinear control systems; optimal control; particle swarm optimisation; search problems; three-term control; MPSO; PID control; Takagi-Sugeno fuzzy model; academic nonlinear system; design method; inertia weight selection method; modified particle swarm optimization; nonlinear process; optimal proportional-integral-derivative controller parameters; random inertia weight algorithm; searching process; self-tuning PID controller; Algorithm design and analysis; Educational institutions; Nonlinear systems; Optimization; PD control; Particle swarm optimization; Tuning; Modified Particle Swarm Optimization; Nonlinear system; PID controller; Takagi-Sugeno;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (WCCIT), 2013 World Congress on

Conference_Location

Sousse

Print_ISBN

978-1-4799-0460-0

Type

conf

DOI

10.1109/WCCIT.2013.6618723

Filename

6618723