Speed Control of Switched Reluctance Motor Using New Hybrid Particle Swarm Optimization
- 1 , India
- 2 Sri Ramakrishna Engineering College, India
Copyright: © 2020 T. V. Mahendiran, K. Thanushkodi and P. Thangam. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Problem statement: The main objective of this research is to obtain the speed control of switched reluctance motor with minimum settling time and without overshoot. Approach: A new algorithm has been developed with the combination of differential evolution and particle swarm optimization and applied for speed control of switched reluctance motor under sudden change in speed. Also speed control of switched reluctance motor was obtained by other artificial intelligence methods such as fuzzy logic controller, fuzzy PI controller and particle swarm optimization based tuning of fuzzy PI controller. Matlab/Simulink environment was used for the simulation. Results: Results are discussed and tabulated based on the performance of the controllers. Conclusion: From the comparison of all above methods, the algorithm has given better results in speed response than other controllers.
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- Switched reluctance motor
- differential evolution
- Particle Swarm Optimization (PSO)
- fuzzy logic controller
- fuzzy PI controller
- PWM inverter