Paper Details: Downloads: 509
Serial Number: P1110549003
Title: Employing Particle Swarm Optimizer and Genetic Algorithms for Optimal Tuning of PID Controllers: A Comparative Study
Authors: Mohammed El-Said El-Telbany
Abstract: The proportional-integral-derivative (PID) controllers were the most popular controllers of this century because of their remarkable effectiveness, simplicity of implementation and broad applicability. However, PID controllers are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. The computational intelligence has purposed genetic algorithms (GA) and particle swarm optimization (PSO) as opened paths to a new generation of advanced process control. These advanced techniques to design industrial control systems are, in general, dependent on achieving optimum performance with the controller when facing with various types of disturbance that are unknown in most practical applications. This paper presents a comparison study of using two algorithms for the tuning of PID-controllers for processes which represents a subsystem of complex industrial processes, known to be non-linear and time variant. Simulation results showed that the PID control tuned by PSO provides an adequate closed loop dynamic for the Ball and Hoop system experiment in wide range operations.
Keywords: Particle swarm optimisation; genetic algorithms, intelligent control; PID control
Journal/Conference: International Journal of Automatic Control and System Engineering
Volume: 7
Issue: 2
Submission Date: 12/1/2005 12:00:00 AM
Review Date: 2/1/2006 12:00:00 AM
Publishing Date: 7/1/2008 12:00:00 AM
Article Downloads: 509
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