Optimal PID Controller design for Automatic Voltage Regulator Systems
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Abstract
- This paper presents optimal PID controller design for Automatic Voltage Regulator systems. This research uses Simulink in MATLAB to compare the experimental result, and finding PID Gain by particle swarm optimization (PSO) are compared to hybrid particle swarm optimization (HPSO). The result of tracking control for AVR systems by selecting the PID gain by using hybrid particle swarm optimization (HPSO) apply to PID algorithm has a better result than other algorithms.
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References
2. J. Kennedy and R. C. Eberhart, "Particle swarm optimization," IEEE International Conference on Neural Networks, Perth, Australia.1995.
3. Xiaoling Wu, and Min Zhong. “A Hybrid Particle Swarm Optimizer,” Second Asia-Pacific Conference on Computational Intelligence and Industrial Applications,2009.
4. Thitiwat Therdbankerd, Peerayot Sanposh, Nattapon Chayopitak, and Hideki Fujita. “Parameter identification of a linear permanent magnet motor using particle swarm optimization,” ECTI-CON. 2010.
5. Automatic Voltage Regulator, Available from: http://www.leonics.co.th/html/th/aboutpower/avr_knowledge.php
6. Zwe-Lee Gaing, "A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System," IEEE transactions on Energy Conversion, Vol.19, No.2, June 2004.