Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
ANN- and PSO-Based Synthesis of On-Chip Spiral Inductors for RF ICs
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Index-based genetic algorithm for continuous optimization problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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The development of power electronics results in a growing need for automatic design and optimization for power electronic circuits (PECs). This paper presents a particle swarm optimization (PSO) approach for the PECs design. The optimization problem is divided into two processes using a decoupled technique and PSO is employed to optimize the values of the circuit components in the power conversion stage (PCS) and the feedback network (FN), respectively. A simple mutation operator is also incorporated into PSO to enhance the population diversity. The algorithm is applied to the optimization of a buck regulator for meeting requirements under large-signal changes and at steady state. Compared with genetic algorithm (GA), PSO can yield more optimized values of circuit components with lower computational effort.