Authors : Mohamed Yaich and Moez Ghariani
Abstract: For electrical drives good dynamic performance is mandatory so as to respond to the changes in command speed and torques. Thus various speed control techniques are being used for real time application. The speed of Switched Reluctance Motor (SRM) can be adjusted to a great extend so as to provide relatively easy control and high performance. There are several conventional and numeric types of controllers intended for controlling the SRM speed and executing various tasks, PID controller, Fuzzy Logic Controller (FLC) or the combination between them, fuzzy-swarm, fuzzy-neural networks, fuzzy-genetic algorithm, fuzzy-ants colony, fuzzy-particle swarm optimization. We would like to clarify in this study the use of Ant Colony Optimization Algorithm (ACO) to optimize the scaling factors of fuzzy logic controller for speed regulation of SRM. The obtained results were simulated on MATLAB/Simulink environment. Excellent flexibility and adaptability as well as high precision and good robustness are obtained by the proposed strategy. The simulations results demonstrate that the proposed ACO-FLC speed controller realize a good dynamic behavior of SRM compared with conventional FLC controller.
Mohamed Yaich and Moez Ghariani, 2017. Metaheuristic Design and Optimization of Fuzzy-Based SRM Speed Controller using Ant Colony Algorithm. Journal of Engineering and Applied Sciences, 12: 7382-7388.