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Evolutionary multi objective optimization process deals with finding out an optimum solution of a problem. Computational efficiency of metaheuristic algorithms is very high. Metaheuristic algorithms are inspired from nature or biological phenomena to solve a variety of optimization problems. The evolutionary optimization has many attractive features. It is very flexible & simple to implement to a wide area applications. Heuristic optimization techniques are mainly of three types(Blum et al.,2003;Boussa et al.,2013). These are swarm, evolutionary and trajectory methods. It has captured interest of many researchers throughout the world for solving complex/nonlinear problems which otherwise difficult to solve. In this paper modified Hybrid Whale Optimization Algorithm with Simulated Annealing (Hybrid mWOASA) technique is proposed. To prove the efficacy of the proposed technique a multiobjective optimization problem involving constraint i.e. control of Switched reluctance motor (SRM) is formulated.
Optimisation techniques are always proved to be a very powerful tool for solving non linear/complex problems. The nonlinear magnetic characteristics (Anwar et al., 2001) associated with SRM results in high torque ripple and noise. The above mentioned features eclipsed its various attaracting characteristics like less cost for maintenance, high torque to mass ratio, simple in construction (Harris, 1989; Lovatt et al.,1997). In most of the application of SRM, it is invariably required to decrease torque ripple of SRM(Majid & Mohammad, 2008).
Different techniques (Shehata, 2013; Kalaivani et al.,2013; Balaji et al.,2012) for controling speed and reducing ripple of the output torque of SRM has been described but due to lack of appropriate model theory & also mathematical complication associated with SRM, it impart challenges for execution. Whereas optimization methods, implement acute details of systems complications or problem with a good-developed models & also provide vast scope for applications. In this work proposed modified Hybrid Whale Optimization Algorithm with Simulated Annealing (Hybrid mWOASA) technique is used for designing of controller for controling speed and minimizing ripple in torque of 4-phase, 75 KW, 8/6 SRM and comparison in performance is made for controller designed on Hybrid mWOASA(Majid et al.,2017), Whale Optimization Algorithm (WOA)(Mirjalili, S., & Lewis, A.,2016).
The remaining part of the paper is planned as follows.