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  • 1.
    Eissa, M. M.
    et al.
    Electrical Power and Machines Engineering, Helwan University, Egypt.
    Virk, Gurvinder S.
    Electrical Power and Machines Engineering, South Westphalia University, Germany.
    AbdelGhany, A. M.
    Electrical Power and Machines Engineering, Helwan University, Egypt.
    Ghith, E. S.
    Optimum Induction Motor Speed Control Technique Using Genetic Algorithm2013In: American Journal of Intelligent Systems, ISSN 2165-8978, E-ISSN 2165-8994, Vol. 3, no 1, p. 1-12Article in journal (Refereed)
    Abstract [en]

    Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using genetic algorithm strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for GA-PI controller.

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