AEE'07 Proceedings of the 6th conference on Applications of electrical engineering
Parallel Particle Swarm Optimization with Adaptive Asynchronous Migration Strategy
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
Solving the flight frequency programming problem with particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A new genetic algorithm for the set k-cover problem in wireless sensor networks
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Index-based genetic algorithm for continuous optimization problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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This correspondence presents pseudocoevolutionary genetic algorithms (GAs) for power electronic circuit (PEC) optimization. Circuit parameters are optimized through two parallel coadapted GA-based optimization processes for the power conversion stage (PCS) and feedback network (FN), respectively. Each process has tunable and untunable parametric vectors. The best candidate of the tunable vector in one process is migrated into the other process as an untunable vector through a migration controller, in which the migration strategy is adaptively controlled by a first-order projection of the maximum and minimum bounds of the fitness value in each generation. Implementation of this method is suitable for systems with parallel computation capacity, resulting in considerable improvement of the training speed. Optimization of a buck regulator for meeting requirements under large-signal changes and at steady state is illustrated. Simulation predictions are verified with experimental results