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Hybrid Modified Whale Optimisation Algorithm Simulated Annealing Technique for Control of SRM

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  • Nutan Saha

    (Veer Surendra Sai University of Technology, India)

  • Sidhartha Panda

    (Veer Surendra Sai University of Technology, India)

Abstract

The evolutionary multiobjective optimization is an identified field for researchers. The goal of evolutionary multiobjective optimization is to optimize several objectives simultaneously. The problem of multiobjective optimisation is more important when the objective function exhibits conflicting characteristics. In this work, metaheuristic techniques such as modified hybrid whale optimization algorithm with simulated annealing (hybrid mWOASA) is proposed for speed control along with minimization of ripple in torque of a 75 KW, 4-phase, 8/6 switched reluctance motor. The proposed method is used for the combined objective of control of speed with minimization of ripple in the output torque of switched reluctance motor (SRM) considering the armature current as constraint. It is noticed that torque ripple coefficient, integral square error of speed (ISE(speed)), and integral square error of current (ISE(current)) reduced significantly by proposed mWOASA technique as compared to hybrid WOASA, WOA.

Suggested Citation

  • Nutan Saha & Sidhartha Panda, 2021. "Hybrid Modified Whale Optimisation Algorithm Simulated Annealing Technique for Control of SRM," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 12(3), pages 123-147, July.
    • Handle: RePEc:igg:jamc00:v:12:y:2021:i:3:p:123-147
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