Selection of PI controller tuning parameters for speed control of PMSM using Biogeography Based Optimization algorithm

This investigation presents optimal selection of Proportional Integral (PI) controller parameters for the speed control in Permanent Magnet Synchronous Motor (PMSM). Optimal selection of PI controller parameters is necessary to improve performance of PMSM. For this purpose, this investigation uses two evolutionary optimization algorithms namely, Real coded Genetic Algorithm (RGA) and Bio-geography Based Optimization (BBO) algorithm. In order to showcase the improvements obtained by PI controller tuned using RGA and BBO algorithms, their performances are compared with the conventional PI controller. Our results indicates that the PI controller tuned using BBO algorithm provides better transient and steady state performance for PMSM.

[1]  Yong Kim,et al.  Implementation of Evolutionary Fuzzy PID Speed Controller for PM Synchronous Motor , 2015, IEEE Transactions on Industrial Informatics.

[2]  Seshadhri Srinivasan,et al.  Supervisory GPC and Evolutionary PI Controller for Web Transport Systems , 2015 .

[3]  S. Singh,et al.  Mutation effects on BBO evolution in optimizing Yagi-Uda antenna design , 2012, 2012 Third International Conference on Emerging Applications of Information Technology.

[4]  Mark Sumner,et al.  A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[5]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[6]  Renato A. Krohling,et al.  Design of optimal disturbance rejection PID controllers using genetic algorithms , 2001, IEEE Trans. Evol. Comput..

[7]  Jesus Doval-Gandoy,et al.  Tuning Method Aimed at Optimized Settling Time and Overshoot for Synchronous Proportional-Integral Current Control in Electric Machines , 2014, IEEE Transactions on Power Electronics.

[8]  Pragasen Pillay,et al.  Modeling, simulation, and analysis of permanent-magnet motor drives. I. The permanent-magnet synchronous motor drive , 1989 .

[9]  R. Krishnan,et al.  Electric Motor Drives: Modeling, Analysis, and Control , 2001 .

[10]  Bruno Allard,et al.  Implementation of Hybrid Control for Motor Drives , 2007, IEEE Transactions on Industrial Electronics.

[11]  Weidong Xiao,et al.  Four-Axis Vector-Controlled Dual-Rotor PMSM for Plug-in Electric Vehicles , 2015, IEEE Transactions on Industrial Electronics.

[12]  Bimal K. Bose,et al.  Modern Power Electronics and AC Drives , 2001 .

[13]  Swagat Pati,et al.  Hybrid differential evolution particle swarm optimisation optimised fuzzy proportional–integral derivative controller for automatic generation control of interconnected power system , 2014 .

[14]  Narayan C. Kar,et al.  Investigation of Integrated Charging and Discharging Incorporating Interior Permanent Magnet Machine With Damper Bars for Electric Vehicles , 2016, IEEE Transactions on Energy Conversion.

[15]  Frede Blaabjerg,et al.  Minimum-Voltage Vector Injection Method for Sensorless Control of PMSM for Low-Speed Operations , 2016, IEEE Transactions on Power Electronics.

[16]  Xavier Blasco Ferragud,et al.  Controller Tuning by Means of Multi-Objective Optimization Algorithms: A Global Tuning Framework , 2013, IEEE Transactions on Control Systems Technology.

[17]  Dehong Xu,et al.  Optimal PID controller design in PMSM servo system via particle swarm optimization , 2005, 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005..

[18]  Sakti Prasad Ghoshal,et al.  Design of Non-uniformly Weighted and Spaced Circular Antenna Arrays with Reduced Side Lobe Level and First Null Beamwidth Using Seeker Optimization Algorithm , 2013, SEMCCO.

[19]  Dan Simon,et al.  Biogeography-based optimization and the solution of the power flow problem , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[20]  Francisco Herrera,et al.  Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis , 1998, Artificial Intelligence Review.

[21]  Marco Mussetta,et al.  Application of modified BBO to microstrip filter optimization , 2013, 2013 IEEE Antennas and Propagation Society International Symposium (APSURSI).

[22]  R. S. D. Wahidabanu,et al.  RGA Based Fractional Order PI Controller Design for Speed Control of IPMSM , 2015 .