Improved Performance of Permanent Magnet Synchronous Motor by using Particle Swarm Optimization Techniques

  • Published : 2009.03.20

Abstract

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.

Keywords

References

  1. N Bianchi, S. Bolognani and M. Zigliotto, "High-Performance PM Synchronous Motor Drive For An Electrical Scooter", IEEE, Trans., on I.A. Vol. 37, No.5, pp. 1348-1355, September/October 2001 https://doi.org/10.1109/28.952510
  2. A. Besharati, W. Lo and K. M. Tsang, "Self-Tuning ofPID Controller Using Newton-Raphson Search Method", IEEE Trans. On I.E., Vol.44, No.5, pp.717-725, 1997 https://doi.org/10.1109/41.633479
  3. S. Wahsh, A., Elwer, M. Khalil, and A. Noureldin, "Tuning PI-Controller Using Particle Swarm Optimization For Control of Permanent Magnet Synchronous Motor", 5th st. Petersburg workshop in Simulation, 5th St. Petersburg, RUSSIA, pp.239-244, 26 June-2July 2005
  4. R.C. Eberhart and J. Kennedy, "A New Optimizer Using Particle Swarm Theory", in proc. of sixth International Symposium On Micro Machine and Human Science (Nagoya, Japan) ,IEEE Service Center, pp. 39-43, 1995
  5. A.P. Engelbrecht and A. Ismail, "Training Product Unit Neural Networks", Stability and Control: Theory and Applications, Vol.2 ,No.1-2 , pp. 59-74, 1999
  6. Y.H. Shi, R. C. Eberhart, "Parameter Selection in Particle Swarm Optimization", The 7th, Annual Conference on Evolutionary Programming , San Diego, USA 1998
  7. Y.H. Shi and R. C. Eberhart, "A Modified Particle Swarm Optimizer", Proceeding of IEEE International Conference on Evolutionary Computation (ICEC'98), Anchorage, pp.69-73, May 1998
  8. S. Wahsh, A., Elwer, M. Khalil,and A. Noureldin, "Intelligent Fuzzy Controller Using Particle Swarm Optimization For Speed Control of Permant Magnet Motor For Electric Vehicle", IECON'03 Conf. Proc. Roanoke, Virginia, USA, pp.1762-1766, 2-6 Nov. 2003
  9. S. Wahsh, A., Elwer, M. Khalil, and A. Noureldin, "Intelligent PI-Controller Using Particle Swarm Optimization For Control Of Permanent Magnet Synchronous Motor For Electric Vehicle", 7th International Symposium on Advanced Vehicle Control A VEC'04, Conf. Proc., HAN University, Amhem, NETHERLAND, pp. 483-489, 23-27Aug. 2004