On the use of pseudo-coevolutionary genetic algorithms with adaptive migration for design of power electronics regulators
Jun J. Zhang, A. Wu, Henry Shu-Hung Chung · 2002
This paper presents the use of pseudo-coevolutionary genetic algorithms for design of power electronics regulators. By using the decoupled optimization technique, the component values of the power conversion stage and feedback network are optimized with two coadapted evolutionary training processes, in which they are classified as two isolated species and are evolved in parallel. Components from one species will asynchronously migrate into collaborations for training another species when that component set has significant enhancement in the overall regulator performance. An adaptive migration rate that improves the overall training process is proposed. This modular approach decentralizes computations and is suitable for network-based optimization. The proposed technique is illustrated with the design of a buck regulator.