Comparison of Parallel Metaheuristics for flux optimization for Induction Motor

An essential aspect of efficiency control of a three-phase induction motor is the ability to generate the optimal magnetic flux required for different operating modes. In this paper, we use the genetic algorithm (GA), the particle swarm optimization algorithm (PSO) and the simulated annealing (SA) to cope with the complexity of the problem and compute feasible and quasi-optimal magnetic flux needed for three-phase induction motors with time varying load and parameters. The characteristics of the optimal magnetic flux are represented in the form of a multi-objective cost function that we developed. We reduce the execution time of our solutions by using the “single-program, multiple-data” parallel programming paradigm and achieve realtime performance on a multi-core CPU. Key-Words: -magnetic flux optimization, genetic algorithm, particle swarm optimization, simulated annealing, parallel computation