Control System Design using Particle Swarm Optimization (PSO)
J. Hamidi
Javad Hamidi, Electrical Engineering Department, Islamic Azad University, Sarakhs Branch, Sarakhs, Iran.
Manuscript received on November 29, 2011. | Revised Manuscript received on December 15, 2011. | Manuscript published on January 05, 2012. | PP: 116-119 | Volume-1 Issue-6, January 2012. | Retrieval Number: F0280111611/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The main purpose of this paper is to select the appropriate weighting matrices for designing of optimal controller using Particle Swarm Optimization (PSO) algorithm as an intelligent procedure. Generally speaking, it is not easy to determine the optimal weighting matrices for a high-dimension control system via analytical methods. There is no direct relation between the elements of weighting matrices and desirable control system characteristics and selecting these weights is performed using time-consuming trial and error method and based on designer experiences. Superior features of PSO method are fast tuning of the parameters, rapid convergence, less computational burden and capability to avoid from local optima. Simulation results demonstrate that our proposed method is more efficient and robust compared with other heuristic method, i.e., the Genetic Algorithm (GA) method.
Keywords: Weighting matrices, Particle Swarm Optimization (PSO), Genetic Algorithm (GA).