Tuning PID Controllers Using Artificial Intelligence Techniques Applied To DC-Motor and AVR System

Authors

  • A. Salem Shams Industry Company (HISENSE)
  • M. A. Mustafa Hassan
  • M. E. Ammar

Keywords:

PID-controller, DC-Motor, AVR system, Genetic Algorithm, Particle Swarm Optimization

Abstract

This paper investigates PID controller tuning using genetic algorithm, modified genetic algorithm and particle swarm optimization techniques. The proposed techniques are compared to PID controllers tuned by the Ziegler-Nichols technique. Closed-loop simulations are conducted using MATLAB and the genetic algorithm toolbox for two applications, a DC-Motor and an Automatic Voltage Regulator (AVR). The overshoots, rise time and settling time with the proposed techniques are shown to be better than those of the conventionally tuned PID controllers.

 

References

K.J. Astrom, T. Hagglund, “PID Controllers: Theory, Design and Tuningâ€, International Society for Measurement and Con., 2nd Ed., pp.200-210, 1995.

A. Jalilvand, A. Kimiyaghalam, A. Ashouri, H. Kord, “Optimal Tuning of PID Controller Parameters on a DC Motor Based on Advanced Particle Swarm Optimization Algorithmâ€, ISSN 2077-3528,IJTPE Journal, 2011.

Guillermo J. Costa, www.powertransmission.com, “Tuning a PID Controllerâ€, April 2011.

Ali Marzoughi, Hazlina Selamat, Mohd Fua’ad Rahmat and Herlina Abdul Rahim, “Optimized proportional integral derivative (PID) controller for the exhaust temperature control of a gas turbine system using particle swarm optimizationâ€, International Journal of the Physical Sciences Vol. 7(5), pp. 720 - 729, 30 January, 2012.

Katsuhiko Ogata, University of Minnesota, “Modern Control Engineering, Fourth Editionâ€, Publisher: Aeeizb, 2002.

A. Zilouchian, M. Jamshidi, “Intelligent Control Systems Using Soft Computing Methodologiesâ€, by CRC Press LLC, 2001.

Mohammed Obaid Ali, S. P. Koh, 1K. H. Chong, S.K.Tiong and Zeyad Assi Obaid, “Genetic Algorithm Tuning Based PID Controller for Liquid-Level Tank Systemâ€, Proceedings of the International Conference on Man-Machine Systems (ICoMMS)11 – 13 October 2009, Batu Ferringhi, Penang, MALAYSIA, 2009.

N. Pillay, “A Particle Swarm Optimization Approach for Tuning of SISO PID Control Loopsâ€, Durban University of Technology, 2008.

A.A. Javadi, R. Farmani, T.P. Tan, “A hybrid intelligent genetic algorithmâ€, www.elsevier.com/locate/aei, Advanced Engineering Informatics 19 (2005) 255–262, 2005.

Andries P. Engelbrecht, “Computational intelligence: an introduction-2nd Ed.â€, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, 2007.

K.E. Parsopoulos and M.N. Vrahatis, “Recent approaches to global optimization problems through Particle Swarm Optimizationâ€, Academic Publishers. Natural Computing 1: 235–306, 2002.

J´anos M´adar, J´anos Abonyi and Ferenc Szeifert, “Interactive Particle Swarm Optimizationâ€, Proceedings of the 2005 5th International Conference on Intelligent Systems Design and Applications (ISDA’05), 2005.

Dian Palupi Rini, Siti Mariyam Shamsuddin and Siti Sophiyati Yuhaniz, “Particle Swarm Optimization: Technique, System and Challengesâ€, International Journal of Computer Applications (0975 – 8887) Volume 14– No.1, January 2011.

A. Marzoughi, H. Selamat, M. F. Rahmat, H. Abdul Rahim, “ Optimized Proportional Integral Derivative (PID) Controller for the Exhaust Temperature Control of a Gas Turbine System Using Particle Swarm Optimizationâ€, International Journal of the Physical Sciences Vol. 7(5), pp. 720-729, 2012.

M. A. Tammam, Faculty of Engineering, Cairo University, Giza, Egypt, “Multi Objective Genetic Algorithm Controller’s Tuning for Load Frequency Control in Power Systemsâ€, 2010.

Anant Oonsivilai and Padej Pao-La-Or, “Optimum PID Controller tuning for AVR System using Adaptive Tabu Searchâ€, 12th WSEAS International Conference on COMPUTERS, Heraklion, Greece, July 23-25, 2008.

A. Bagis, “Determination of the PID Controller Parameters by Modified Genetic Algorithm for Improved Performanceâ€, Journal of Information Science and Engineering 23, 1469-1480 (2007).

N. Thomas, Dr. P. Poongodi, “Position Control of DC Motor Using Genetic Algorithm Based PID Controllerâ€, Proceedings of the World Congress on Engineering 2009 Vol II, London, U.K., 2009.

A. Jalilvand, A. Kimiyaghalam, A. Ashouri and H. Kord, “OPTIMAL TUNING OF PID CONTROLLER PARAMETERS ON A DC MOTOR BASED ON ADVANCED PARTICLE SWARM OPTIMIZATION ALGORITHMâ€, International Journal on “Technical and Physical Problems of Engineering†(IJTPE) Published by International Organization on TPE (IOTPE). December 2011.

Zwe-Lee Gaing, “A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR Systemâ€, IEEE Transactions on Energy Conversion, Vol. 19, NO. 2, JUNE 2004.

Ching-Chang Wong, Shih-An Li and Hou-Yi Wang, “Optimal PID Controller Design for AVR Systemâ€, Tamkang Journal of Science and Engineering, Vol. 12, No. 3, pp. 259_270 (2009).

S. F. Kheder, “Genetic Algorithm Based Controller’s Tuning for Linear and Nonlinear Automatic Voltage Regulator in Electrical Power Systemâ€, M.Sc. thesis, Faculty of Engineering, Cairo University 2013.

S. M. A. Mohammadi, A.A. Gharaveisi, M. Mashinchi, and S.M.R. Rafiei, Senior Member, IEEE, “New Evolutionary Methods for Optimal Design of PID Controllers for AVR Systemâ€, Paper accepted for presentation at IEEE Bucharest Power Tech Conference, June 28th - July 2nd, Bucharest, Romania, 2009.

Downloads

Published

2014-04-25

How to Cite

Salem, A., Hassan, M. A. M., & Ammar, M. E. (2014). Tuning PID Controllers Using Artificial Intelligence Techniques Applied To DC-Motor and AVR System. Asian Journal of Engineering and Technology, 2(2). Retrieved from https://www.ajouronline.com/index.php/AJET/article/view/1121

Issue

Section

Articles