Particle Swarm Optimization for Position Control of Induction Motor

Abstract:

This paper proposes a position control of induction motor using particle swarm optimization (PSO) and fuzzy phase plane controller. Fuzzy membership functions, phase plane theory and the PSO are employed to design the proposed controller (FPPC) for controlling the position of an induction motor, based on the desired specifications. The proposed FPPC has merits of rapid response, simply designed fuzzy logic control and an explicitly designed phase plane theory. Simulations and experimental results reveal that the proposed FPPC is superior in optimal position control to conventional PI controller.

• Periodical: Advanced Materials Research (Volume 918)
• Pages: 231-236
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.918.231
• Online since: April 2014
• Authors: Chao Lung Chiang*
• Keywords: Fuzzy Phase Plane, Particle Swarm Optimization (PSO), Position Control

References

[1] Z. Libo, J. E. Fletcher, B.W. Williams and H. Xiangning, A Novel Direct Torque Control Scheme for a Sensorless Five-Phase Induction Motor Drive, IEEE Transactions on Industrial Electronics, vol. 58, issue 2, p.503 – 513, (2011).

DOI: 10.1109/tie.2010.2047830

[2] A.M. Bazzi, A. Dominguez-Garcia and P.T. Krein, Markov Reliability Modeling for Induction Motor Drives Under Field-Oriented Control, IEEE Transactions on Power Electronics, vol. 27, Issue 2, p.534 – 546, (2012).

DOI: 10.1109/tpel.2011.2168543

[3] C.M. Liaw and F.J. Lin, A Discrete Adaptive Induction Position Servo Drive, IEEE Trans. on Energy Conversion, Vol. 8, No. 3, pp.350-356, (1993).

DOI: 10.1109/60.257044

[4] J.Y. Sun, W. Shi and Z.C. Wang, The application of the phase plane in the tuning method for fuzzy PID, in Proc. 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet), p.1381 – 1385, (2012).

DOI: 10.1109/cecnet.2012.6202039

[5] W.C. Wu and M.S. Tasi, Application of Enhanced Integer Coded Particle Swarm Optimization for Distribution System Feeder Reconfiguration, IEEE Trans. on Power Systems, Vol. 26, Issue. 3, pp.1591-1599, (2011).

DOI: 10.1109/tpwrs.2010.2094212

[6] Y. Wang andY. Yang, Particle swarm with equilibrium strategy of selection for multi-objective optimization, European Journal of Operational Research, Vol. 200, Issue1, pp.187-197, (2010).

DOI: 10.1016/j.ejor.2008.12.026

[7] P.C. Krause, Analysis of Electric Machinery, NY, McGraw-Hill, (1987).

[8] C.M. Liaw and F.J. Lin, Position Control with Fuzzy adaptation for Induction Servomotor Drive, IEE Proc. Electr. Power Appl., Vol. 142, No. 6, pp.397-404, (1995).

DOI: 10.1049/ip-epa:19952209

[9] B.C. Kuo, Automatic Control System, NY, John Wiley & Sons, (1995).

[10] C.L. Chiang, Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels, IEEE Transactions on Power Systems, Vol. 20, No. 4, pp.1690-1699, Nov. (2005).

DOI: 10.1109/tpwrs.2005.857924

[11] C.L. Chiang, Immune-based Algorithm for Power Economic Emission Dispatch, International journal Applied Mechanics and Materials, Vol. 470, pp.785-789, (2013).

DOI: 10.4028/www.scientific.net/amm.470.785