Genetic algorithm tuned PI controller on PMSM simplified vector control

Abstract

A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar performance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.

Keywords

simplified vector control / conventional field oriented control / permanent magnet synchronous motor / genetic algorithm / PI controller

References

[1] LuD, LiK, ZhaoG. Speed control for a permanent magnet synchronous motor with an adaptive self-tuning uncertainties observer [C]. Life System Modeling and Intelligent Computing, 2010BerlinSpringer379-389

[2] JatothR K, RajasekharA. Speed control of pmsm by hybrid genetic artificial bee colony algorithm [C]. IEEE International Conference on Communication Control and Computing Technologies, 2010RamanathapuramIEEE Press241-246

[3] KhaterF, ShaltoutA, HendawiE, Abu El-SebahM. PI controller based on genetic algorithm for pmsm drive system [C]. IEEE International Symposium on Industrial Electronics, 2009SeoulIEEE Press250-255

[4] ChebreM, MeroufelA, BendahaY. Speed control of induction motor using genetic algorithm-based PI controller indirect field-oriented control of the IM [J]. Acta Polytechnica Hungarica, 2011, 8(6): 141-153

[5] ZareJ. Vector control of permanent magnet synchronous motor with surface magnet using artificial neural networks [C]. 2008 43rd International Universities Power Engineering Conference, 2008PadovaIEEE Press1-4

[6] BilginM Z, ÇakirB. Neuro-PID position controller design for permanent magnet synchronous motor [C]. Advances in Natural Computation, 2006Berlin HeidelbergSpringer418-426

[7] KarabacakM, EskikurtH I. Speed and current regulation of a permanent magnet synchronous motor via nonlinear and adaptive backstepping control [J]. Mathematical and Computer Modelling, 2011, 53(9/10): 2015-2030

[8] LüB-f, ZhangG-xiang. Simulation and research of control-system for PMSM based on sliding mode control [J]. Physics Procedia, 2012, 33: 1280-1285

[9] ErbaturK, KaynakM O, SabanovicA. A study on robustness property of sliding-mode controllers: A novel design and experimental investigations [J]. IEEE Transactions on Industrial Electronics, 1999, 46(5): 1012-1018

[10] RahidehA, RahidehA, KarimiM, ShakeriA, AzadiM. High performance direct torque control of a pmsm using fuzzy logic and genetic algorithm [C]. 2007 IEEE International Electric Machines & Drives Conference, 2007AntalyaIEEE Press932-937

[11] YuJ, KimS, LeeB. Fuzzy-logic-based vector control scheme for permanent-magnet synchronous motors in elevator drive applications [J]. IEEE Transactions on Industrial Electronics, 2007, 54(4): 2190-2200

[12] UddinM N, AbidoM A, RahmanM A. Real-time performance evaluation of a genetic algorithm based fuzzy logic controller for interior permanent magnet synchronous motor drive [C]. Second International Conference on Electrical and Computer Engineering, 2002Salt Lake CityIEEE Press26-28

[13] DeyA, SinghB, DwivediB, ChandraD. Vector controlled induction motor drive using genetic algorithm tuned PI speed controller [J]. Electrical Power Quality and Utilisation, 2009, 15(1): 3-8

[14] DumanS, MadenD, GüvençU. Determination of the PID controller parameters for speed and position control of DC motor using gravitational search algorithm [C]. International Conference on Electrical and Electronics Engineering (ELECO), 2011BursaIEEE Press225-229

[15] BedwaniW A, IsmailO M. Genetic optimization of variable structure PID control systems [C]. Proceedings ACS/IEEE International Conference on Computer Systems and Applications, 2001BeirutIEEE Press27-30

[16] KrishnanRElectric Motor Drives: Modeling Analysis and Control [M], 2001New JerseyPrentice Hall

[17] SugimotoH, KoyamaM, TamaiS. Theory and Application of AC Servo System [M]. New York: General Electronics, 199493-98

[18] ColeyD AAn introduction to genetic algorithm for scientists and engineers [M], 1999SingaporeWorld Scientific Publishing