A particle-swarm-based approach for optimum design of BELBIC controller in AVR system

Author

Valizadeh, Sima ; Jamali, Mohammad-Reza ; Lucas, Caro

Author_Institution

Dept. of Electr. Eng., Univ. of Tehran, Tehran

fYear

2008

Firstpage

2679

Lastpage

2684

Abstract

In this paper, Particle Swarm Optimization algorithm is applied to design an optimum intelligent controller based on brain emotional learning. BELBIC controller is tuned to improve the time domain parameters such as percent overshoot, steady state error, settling time and rise time of the step response of an Automatic Voltage Regulator. Also the convergence characteristic of fitness function averaged over the whole particles in each generation is investigated. PSO-BELBIC performance is compared with the classic PSO-PID controller.

Keywords

control system synthesis; intelligent control; particle swarm optimisation; voltage regulators; AVR system; BELBIC controller design; automatic voltage regulator; brain emotional learning; intelligent controller; particle swarm optimization algorithm; steady state error; Algorithm design and analysis; Automatic control; Brain modeling; Control systems; Nonlinear control systems; Optimal control; Particle swarm optimization; Power system control; Power system dynamics; Power system modeling; AVR system; BELBIC controller; Emotional learning; optimal control; particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation and Systems, 2008. ICCAS 2008. International Conference on

Conference_Location

Seoul

Print_ISBN

978-89-950038-9-3

Electronic_ISBN

978-89-93215-01-4

Type

conf

DOI

10.1109/ICCAS.2008.4694214

Filename

4694214