Speed Control of Permanent Magnet Synchronous Motor Using Evolutionary Fuzzy PID Controller
Authors: M. Umabharathi, S. Vijayabaskar
Abstract:
Evolutionary Fuzzy PID Speed Controller for Permanent Magnet Synchronous Motor (PMSM) is developed to achieve the Speed control of PMSM in Closed Loop operation and to deal with the existence of transients. Consider a Fuzzy PID control design problem, based on common control Engineering Knowledge. If the transient error is big, that Good transient performance can be obtained by increasing the P and I gains and decreasing the D gains. To autotune the control parameters of the Fuzzy PID controller, the Evolutionary Algorithms (EA) are developed. EA based Fuzzy PID controller provides better speed control and guarantees the closed loop stability. The Evolutionary Fuzzy PID controller can be implemented in real time Applications without any concern about instabilities that leads to system failure or damage.
Keywords: Evolutionary Algorithm (EA), Fuzzy system, Genetic Algorithm (GA), Membership, Permanent Magnet Synchronous Motor (PMSM).
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339175
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[1] M. Preindl and S. Bolognani (2013), ‘Model predictive direct torque control with finite control set for PMSM drive systems, Part 2: Field weakening operation,’ IEEE Trans. Ind. Inf., vol. 9, no. 2, pp. 648–657.
[2] N. T.-T. Vu, D.-Y.Yu, H. H. Choi, and J.-W. Jung (2013), ‘T-S fuzzy model based sliding mode control for surface mounted permanent magnet synchronous motors considering uncertainties,’ IEEE Trans. Ind. Electron., vol. 60, no. 10, pp. 4281–4291.
[3] K. Jezernik, R. Horvat, and M. Curkovic (2013), ‘A switching control strategy for the reduction of torque ripple for PMSM,’ IEEE Trans. Ind. Inf., vol. 9, no. 3, pp. 1272–1279.
[4] G. Liu, L. Chen, W. Zhao, Y. Jiang, and L. Qu (2013), ‘Internal model control of permanent magnet synchronous motor using support vector machine generalized inverse,’ IEEE Trans. Ind. Inf., vol. 9, no. 2, pp. 890–898.
[5] M. Morawiec (2013), ‘The adaptive backstepping control of permanent magnet synchronous motor supplied by current source inverter,’ IEEE Trans. Ind. Inf., vol. 9, no. 2, pp. 1047–1055.
[6] H. H. Choi and J.-W. Jung (2013), ‘Discrete time fuzzy speed regulator design for PM synchronous motor,’ IEEE Trans. Ind. Electron., vol. 60, no. 2, pp., 600–607.
[7] T. D. Do, H. H. Choi, and J.-W. Jung (2012), ‘SDRE based near optimal control system design for PM synchronous motor,’ IEEE Trans. Ind. Electron., vol. 59, no. 11, pp. 4063–4074.
[8] H. H. Choi, N. T.-T. Vu, and J.-W. Jung (2011), ‘Digital implementation of an adaptive speed regulator for a PMSM,’ IEEE Trans. Power Electron., vol. 26, no. 1, pp. 3–8.
[9] H. H. Choi, V. Q. Leu, V. Q., Y.-S. Choi, and J.-W. Jung (2011), ‘Adaptive speed controller design for a permanent magnet synchronous motor,’ IET Electr. Power Appl., vol. 5, no. 5, pp. 457–464.
[10] J.-W. Jung, Y.-S. Choi, V. Q. Leu, and H. H. Choi (2011), ‘Fuzzy PI type current controllers for permanent magnet synchronous motors,’ IET Electr. Power Appl., vol. 5, no. 1, pp. 143–152.
[11] Y.-S. Kung, C.-C.Huang, and M.-H. Tsai (2009), ‘FPGA realization of an adaptive fuzzy controller for PMLSM drive,’ IEEE Trans. Ind. Electron., vol. 56, no. 8, pp. 2923–2932.
[12] S. Li and Z. Liu (2009), ‘Adaptive speed control for permanent-magnet synchronous motor system with variations of load inertia,’ IEEE Trans. Ind. Electron., vol. 56, no. 8, pp. 3050–3059.
[13] C.-K. Lin, T.-H. Liu, and S.-H. Yang (2008), ‘Nonlinear position controller design with input-output linearisation technique for an interior permanent magnet synchronous motor control system,’ IET Power Electron., vol. 1, no. 2, pp. 14–26.
[14] A. V. Topalov, G. L. Cascella, V. Giordano, F. Cupertino, and O. Kaynak (2007), ‘Sliding mode neuro-adaptive control of electric drives,’ IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 671–679.
[15] M. Cheng, Q. Sun, and E. Zhou (2006), ‘New self-tuning fuzzy PI control of a novel doubly salient permanent magnet motor drive,’ IEEE Trans. Ind. Electron., vol. 53, no. 3, pp. 814–821.