Evolutionary Computation Techniques Based Optimal PID Controller Tuning

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2013 by IJETT Journal
Volume-4 Issue-6                      
Year of Publication : 2013
Authors : Sulochana Wadhwani , Veena Verma


Sulochana Wadhwani , Veena Verma."Evolutionary Computation Techniques Based Optimal PID Controller Tuning". International Journal of Engineering Trends and Technology (IJETT). V4(6):2529-2534 Jun 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.


The main aim of this paper is to analyse the implementation of two Evolutionary Computation (EC) techniques viz. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for optimal tuning of PID controllers parameters and enumerate their advantages over the conventional tuning methodologies. The two techniques were implemented and analysed on a third order plant model of a DC servomotor with the aim of developing a position controller. The results obtained fr om GA and PSO algorithms were compared with that obtained from Ziegler Nichols method. It was found that the evolutionary computation techniques outperformed traditional tuning practices of Zeigler - Nichols at tuning of PID controllers .


[1]. Dorf and Bishop, Modern Control Systems , 9th Ed., Prentice - Hall, Inc. 2001 .
[2]. V. Rajinikanth and K. Latha, Tuning and Retuning of PID Controller for Unstable Systems Using Evolutionary Algorithm , Research Article , International Scholarly Research Network, Volume 2012, Article ID 693545, doi:10.5402/2012/693545
[3]. Ömer Gündo?du, optimal - tuning of PID controller gains using genetic algorithms , Journal of Engineering Sciences, pp 131 - 135, 2005 11(1).
[4]. Bhawna Tandon, Randeep Kaur, genetic algorithm based parameter tuning of pid controller for composition control system, International Journal of Engineering Science and Technology, ISSN:0975 - 5462, Vol. 3 No. 8 August 2011, pp 6705 - 6711 .
[5]. F. M. Amaral, Ricardo Tanscheit, Marco A. C. Pacheco, Tuning PID Controllers through Genetic Algorithms, WSES International Conference on Evolutionary Computation, Feb 12 - 14, 2001, pp 6121 - 6124 .
[6]. Neenu Thomas, Dr. P. Poongodi, Position Control of DC Motor Using Genetic Algorithm Based PID Controller, Proceedings of the World Congress on Engineering 2009 (ISBN: 978 - 988 - 18210 - 1 - 0) Vol II WCE 2 009, July 1 - 3, 2009, London, U.K .
[7]. Harinath Babu Kamepalli, The optimal basics for Gas, IEEE Potentials, 0278 - 6648/01/$10.00 © 2001 IEEE, April/May 2001 pp 25 - 27 .
[8]. Tom V. Mathew, Genetic Algorithm, Lecture notes http://www.civil.iitb.ac.in/tvm/2701_dga/2701 - ga - notes/ gadoc/ gadoc.html .
[9]. http://en.wikipedia .org/wiki/Evolutionary_computation
[10]. M. Molenaar, P. Nijdam, Y. Yan, W.A. Klop, Tuning a PID controller: Particle Swarm Optimization versus Genetic Algorithms , http://www.martinm.nl/attachments/028_paper_ tuning_ a_PID_controller.pdf
[11]. Sulochana Wadhwani, Veena Verma, Rekha Kushwah, “ Design and Tuning of PID Controller Parameters based on Fuzzy Logic and Genetic Aalgorithm ” , Int. Conf. on Soft Computing, Artificia l Intelligence, Pattern Recognition, Biomedical Engineering and Associated Technologies (SAP - BEATS) 23 - 24 Feb ,2013 ”, Department of Electrical Engineering, MBM Eng. College Jai Narain Vyas University,Jodhpu

PID Tuning , Evolutionary Computation, Evolutionary Algorithm, Genetic Algorithm, Swarm Intelligence, Particle Swarm Optimization