Abstract

The position of Brushless Direct Current (BLDC) rotor is determined by measuring the changes in the Back-EMF. Sensorless control method reduces the cost of the motor as it does not need sensors. This paper presents Bio-inspired optimization technique (Particle Swarm Optimization algorithm) and classical methods of tuning PID control parameters for the automatic speed tracking of BLDC motor. The BLDC is modelled in Simulink in Matlab and Back-EMF waveforms are modelled as a function of rotor position. The proposed methods are effective in reducing the steady state error, rise time, settling time, and peak overshoot. The classical methods such as Ziegler-Nichols (Z-N), Tyreus-Luyben (T-L) methods, and Particle Swarm Optimization (PSO) techniques based on effective objective function Integral Absolute Error (IAE) are proposed for the optimal tuning of PID controller parameters. The results obtained from Particle Swarm Optimization technique are compared with the classical methods.

Keywords
Brushless Direct Current Motor, Sensorless Control, Particle Swarm Optimization, PID Controller.
How to Cite this Article?
Merugumalla,M.K., and Navuri,P.K. (2017). Sensorless Control of BLDC Motor using Bio-Inspired Optimization Algorithm and Classical Methods of Tuning PID Controller. i-manager’s Journal on Instrumentation and Control Engineering, 5(1), 16-23.
References
[1]. R. Krishnan, (2001). Electric Motor Drives, Modeling Analysis and Control. Prentice Hall Publications.
[2]. B.K. Bose, (2001). Modern Power Electronics and AC Drives. Prentice Hall PTR Publications.
[3]. Chenjun Cui, Gang Liu, Kun Wang, and Xinda, (2015). “Sensorless Drive for High-Speed Brushless DC” In IEEE Transactions on Power Electronics, Vol. 30, No. 6, pp. 3275- 3285.
[4]. Marcin Baszynski, and Stanislaw Pirog, (2014). “A Novel Speed Measurement Method for a High-Speed BLDC Motor based on the Signals from the Rotor Position Sensor”. In IEEE Transactions on Industrial Informatics, Vol. 10, No. 1, pp. 84-91.
[5]. Alin Stirban, Ion Boldea, and Gheorghe Daniel Andreescu, (2012). “Motion-Sensorless Control of BLDC-PM Motor with Offline FEM-Information-Assisted Position and Speed Observer”. In IEEE Transactions on Industry Applications, Vol. 48, No. 6, pp. 1950-1958.
[6]. Chung-Wen Hung, Cheng-Tsung Lin, Chih-Wen Liu, and Jia-Yush Yen, (2007). “A Variable-Sampling Controller for Brushless DC Motor Drives with Low-Resolution Position Sensors”. In IEEE Transactions on Industrial Electronics, Vol. 54, No. 5, pp. 2846-2852.
[7]. Tae-Hyung Kim, and Mehrdad Ehsani, (2004). “Sensorless Control of the BLDC Motors from Near-Zero to High Speeds”. In IEEE Transactions on Power Electronics, Vol. 19, No. 6, pp. 1635-1645.
[8]. Huazhang Wang, (2012). “Design and Implementation of Brushless DC Motor Drive and Control System”. In 2012 International Workshop on Information and Electronics Engineering (IWIEE), Procedia Engineering (Elsevier), Vol. 29, pp. 2219-2224.
[9]. Mahdi Mansouri, Hr. Aghay Kaboli, Jalil Ahmadian, and Jeyraj Selvaraj, (2012). “Hybrid Neuro-Fuzzy - PI Speed Controller for BLDC Enriched with an Integral Steady State Error Eliminator”. In 2012 IEEE International Conference on Control System, Computing and Engineering, pp. 23-25, Penang.
[10]. L. Gao, H. Gao, and C. Zhou, (2004). “Particle Swarm Optimization based algorithm for machining parameter optimization”. In Proceedings of the 5 World Congress on Intelligent Control and Automation, Vol. 4, No. 15-19, pp. 2867-2871.
[11]. C.L. Lin, and H.Y. Jan, (2002). “Revolutionarily multi objective PID control for linear brushless DC motor”. In Proc. of IEEE Int. Conf.Industrial Elect. Society, Vol. 3, pp. 2033- 2038.
[12]. R. Jan, C. Tseng, and R. Liu, (2008). “Robust PID control design for permanent magnet synchronous motor: A genetic approach”. Electric Power Systems Research (Elsevier), Vol. 78, No. 7, pp. 1161–1168.
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