Multiobjective Optimisation by PSO for Switched Reluctance Motor (SRM) Drive

Jayanta Mukherjee, Sumana Chowdhuri

2014

Abstract

Switched Reluctance Motor (SRM), which has many advantages like Induction machine exhibits very nonlinear characteristics and high torque ripple, the only disadvantages of this machine. Its torque ripple is dependent on the current profile and also on the turn on and turns off angle of phase excitation and the speed is dependent on the current command. This work presents one of the Heuristic approaches like Particle Swarm optimization (PSO) to determine the optimum proportional-integral (PI) controller parameters and turn on and turn off angles, for minimum torque ripple with optimum torque profile SRM drive. These offline tuning methods are implemented for the model of a SRM in MATLAB. It has been observed that by optimizing the controller parameters of a SRM drive with PSO the performance of the controller is improved.

References

  1. T J E Miller, Electronic Control of Switched Reluctance Machines, Newnes, Newnes ower Engineering Series, 2004, ISBN 0 7506 50737.
  2. Hameyer, Mitigation of the Torque Ripple of a Switched Reluctance MotorThrough a Multiobjective Optimization, IEEE Transactions on Magnetics, Vol. 44, No. 6, June 2008, pp 1018-1024.
  3. Satit Owatchaiphong, Nisai H. Fuengwarodsakul, MultiObjective Based Optimization for Switched Reluctance Machines Using Fuzzy and Genetic Algorithms, IEEE conference Proceedings PEDS2009, pp 1530-1532.
  4. M. Balaji and Dr.V.Kamaraj, Design Optimization of Switched Reluctance Machine using Particle Swarm Optimization, International Conference on Electrical Energy Systems (ICEES), 2011, pp164-169.
  5. Kapsiotis,George., Tzafestas, Spyros., “PID self -tuning control combining pole placement and parameter optimization features (original research article) Mathematics and Computers in Simulation”, Volume 37, Issues2-3,30 November1994, Pages133-142.
  6. Eberhart,R., Kennedy,J., “Particle swarm optimization,” in Proc. IEEE Int. Conf. Neural Networks, vol. IV, Perth, Australia, 1995, pp. 1942-1948.
  7. Panda, Sidhartha., Padhy, “Comparison of particle swarm optimization and genetic algorithm for TCSC-based controller design”, Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Uttaranchal 247667, India, International journal of Electrical and Electronics Engineering 1:5 2007.
  8. Mehdi, Nasri., Hossein Nezamabadi-pour, and Malihe Maghfoori, “A PSO Based Optimum Design of PID Controller for a Linear Brushless DC Motor”, in World Academy of Science, Engineering and Technology 26 2007.
  9. Gaing, Z.-L., “A particle swarm optimization approach for optimum design of PID controller in AVR system,” IEEE Trans. Energy Conversion, vol.19, pp. 384-391, June 2004.
  10. Banerjee, T., Choudhuri, S., Bera, J.N, Maity,A., “Off-line optimization of PI and PID controller for a vector controlled induction motor drive using PSO”, (ICECE), 2010 International Conference on Electrical and Computer Engineering, 18-20 Dec. 2010, On Page(s): 74 - 77, ISBN: 978- 1-4244-6277-3.
  11. Ogata, Katshuhiko, “Modern Control Engineering” (PHI Learing Private Limited, Fifth edition,2010).
Download


Paper Citation


in Harvard Style

Mukherjee J. and Chowdhuri S. (2014). Multiobjective Optimisation by PSO for Switched Reluctance Motor (SRM) Drive . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 391-396. DOI: 10.5220/0005101403910396


in Bibtex Style

@conference{icinco14,
author={Jayanta Mukherjee and Sumana Chowdhuri},
title={Multiobjective Optimisation by PSO for Switched Reluctance Motor (SRM) Drive},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={391-396},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005101403910396},
isbn={978-989-758-039-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Multiobjective Optimisation by PSO for Switched Reluctance Motor (SRM) Drive
SN - 978-989-758-039-0
AU - Mukherjee J.
AU - Chowdhuri S.
PY - 2014
SP - 391
EP - 396
DO - 10.5220/0005101403910396