Optimal Control And Design Of PMBLDC Motor Using NSGA-II Multi-objective Algorithms
Keywords:
Optimal design, Speed control, DC motor, Non-dominated sorting genetic algorithms, Multi objective particle swarm optimization.Abstract
This study presents an optimal design and a control shame for PMBLDC motor based on multi-objective non-dominated sorting genetic algorithms NSGA-II which is able to optimum both volume and cost of constructing of dc motor and tune the PID controller parameters simultaneously in order of trade-off optimal solutions. Single objective population based method such as genetic algorithm or particle swarm optimization have only one solution in single run but multi-objective optimization can find various solutions in a single run. This paper deals with some objective functions. The cost function include of step response characteristic of motor speed, building cost and its volume that should be minimized simultaneously. To reach this goal in this application the NSGA-II and MOPSO are used for the first time. The results of simulations show the validation of this methods.
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