A Comparative Study of Genetic Algorithm and Particle Swarm Optimization based Optimizations of PID Controller Parameters
Jaison John1, C. Sathish Kumar2
1Jaison John, Department of EEE, Government Engineering College, Idukki, India.
2Dr. C. Sathish Kumar, Department of Computer Applications, Rajiv Gandhi Institute of Technology, Kottayam, India.
Manuscript received on November 02, 2014. | Revised Manuscript received on November 04, 2014. | Manuscript published on November 05, 2014. | PP: 73-76 | Volume-4 Issue-5, November 2014. | Retrieval Number: E2426114514/2014©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: Proportional-Integral-Derivative (PID) control is the most commonly used algorithm for industrial control. The process of computing and setting the optimal gains for P, I and D to get an ideal response from a control system, called as tuning, is a very difficult task. In this paper, two types of nature inspired algorithms genetic algorithm (GA) and particle swarm optimization (PSO) techniques are used for optimizing the PID parameters. These techniques have been observed to be capable of locating high performance areas in complex domains without experiencing the difficulties associated with high dimensionality or false optima. Hard disk drive read/write head servo control system and DC motor control are used in the simulation study for depicting the efficacy of the proposed methods. PID controllers optimized using GA and PSO are observed to provide better time domain performance in comparison with conventionally used tuning method of Ziegler-Nichols.
Keywords: Genetic Algorithm, Particle Swarm Optimization, Tuning of PID Controller, Ziegler-Nichols.