An Application of Novel Nature-Inspired Optimization Algorithms to Auto-Tuning State Feedback Speed Controller for PMSM

This paper focuses on application of novel nature-inspired optimization algorithms to auto-tuning state feedback speed controller (SFC) for permanent magnet synchronous motor (PMSM). An artificial bee colony (ABC) algorithm and a flower pollination algorithm (FPA) are employed to obtain weighting matrices Q and R elements in linear quadratic regulator (LQR) optimization process. Information concerning principles of operation and influence of the control parameters on the both optimization algorithms are presented. Necessary modifications of ABC and FPA required for their successful application in a field of automatic control of electrical drive are depicted, including introduction of constraint-handling method that assures proper and safety operation of the motor and construction of performance indexes to provide the fulfillment of specified requirements. To the best of our knowledge, this is the first time that FPA is applied to auto-tuning process of SFC. On the basis of numerous tests, including simulation and experimental results, it is shown that the ABC is the most useful among the two optimization algorithms to obtain a better performance of the PMSM drive.

[1]  Carlos A. Coello Coello,et al.  Constraint-handling in nature-inspired numerical optimization: Past, present and future , 2011, Swarm Evol. Comput..

[2]  Michal Brasel.  A gain-scheduled multivariable LQR controller for permanent magnet synchronous motor , 2014, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR).

[3]  Narayan C. Kar,et al.  Genetic algorithm based current optimization for torque ripple reduction of interior PMSMs , 2016, 2016 XXII International Conference on Electrical Machines (ICEM).

[4]  Kundan Kumar.  Efficiency improvement of three phase traction inverter through GaN devices for PMSM , 2016, 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES).

[5]  Frede Blaabjerg,et al.  Efficiency Improvement of Variable Speed Electrical Drives for HVAC Applications , 2000 .

[6]  Moataz Elsied,et al.  Highly efficient drive system based on SiC MOSFETs for high power electric transportation , 2017, 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG).

[7]  S. Bolognani,et al.  Model Predictive Direct Speed Control with Finite Control Set of PMSM Drive Systems , 2013, IEEE Transactions on Power Electronics.

[8]  Ilya Pavlyukevich.  Lévy flights, non-local search and simulated annealing , 2007, J. Comput. Phys..

[9]  Lech M. Grzesiak,et al.  Particle Swarm Optimization of the Multioscillatory LQR for a Three-Phase Four-Wire Voltage-Source Inverter With an $LC$ Output Filter , 2015, IEEE Transactions on Industrial Electronics.

[10]  Dervis Karaboga,et al.  Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems , 2007, IFSA.

[11]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[12]  Mario Marchesoni,et al.  PSO-Based Self-Commissioning of Electrical Motor Drives , 2015, IEEE Transactions on Industrial Electronics.

[13]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[14]  M. Safiuddin,et al.  Magnitude and symmetric optimum criterion for the design of linear control systems-what is it and does it compare with the others? , 1988, Conference Record of the 1988 IEEE Industry Applications Society Annual Meeting.

[15]  Michael W. Degner,et al.  DC bus capacitor discharge of permanent magnet synchronous machine drive systems for hybrid electric vehicles , 2017, 2016 IEEE Applied Power Electronics Conference and Exposition (APEC).

[16]  Narayan C. Kar,et al.  Investigation of Permanent-Magnet Motor Drives Incorporating Damper Bars for Electrified Vehicles , 2015, IEEE Transactions on Industrial Electronics.

[17]  T. Sato,et al.  Auto-tuning of two-degree-of-freedom motor control for high-accuracy trajectory motion , 1996 .

[18]  Lech M. Grzesiak,et al.  PMSM servo‐drive control system with a state feedback and a load torque feedforward compensation , 2012 .

[19]  Lech M. Grzesiak,et al.  Particle swarm optimization of artificial-neural-network-based on-line trained speed controller for battery electric vehicle , 2012 .

[20]  Kittithuch Paponpen,et al.  LQR state feedback controller based on particle swarm optimization for IPMSM drive system , 2015, 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA).

[21]  Lech M. Grzesiak,et al.  Permanent magnet synchronous motor discrete linear quadratic speed controller , 2011, 2011 IEEE International Symposium on Industrial Electronics.

[22]  I. Boldea,et al.  Control issues in adjustable speed drives , 2008, IEEE Industrial Electronics Magazine.

[23]  Lech M. Grzesiak,et al.  Artificial bee colony based auto-tuning of PMSM state feedback speed controller , 2016, 2016 IEEE International Power Electronics and Motion Control Conference (PEMC).

[24]  Dervis Karaboga,et al.  A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems , 2011, Appl. Soft Comput..

[25]  Lech M. Grzesiak,et al.  Constrained State Feedback Speed Control of PMSM Based on Model Predictive Approach , 2016, IEEE Transactions on Industrial Electronics.

[26]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[27]  Cheng-Tsung Liu,et al.  Design of a Coaxially Magnetic-Geared Linear Actuator for Electric Power Steering System Applications , 2016, 2016 International Conference of Asian Union of Magnetics Societies (ICAUMS).

[28]  D. Boroyevich,et al.  Implementation and Sensorless Vector-Control Design and Tuning Strategy for SMPM Machines in Fan-Type Applications , 2006, Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting.

[29]  Imam Robandi,et al.  Optimal feedback control design using genetic algorithm in multimachine power system , 2001 .

[30]  Michael Athans,et al.  Gain and phase margin for multiloop LQG regulators , 1976, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

[31]  Xin-She Yang,et al.  Flower Pollination Algorithm for Global Optimization , 2012, UCNC.