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Clonal selection algorithm in power filter optimization

Inspired by natural immune mechanisms, artificial immune optimization (AIO) methods have been successfully applied to deal with numerous challenging optimization problems with superior performances over classical optimization techniques. Clonal selection algorithm (CSA) is one of the most widely employed immune-based approaches for handling those optimization tasks. In this paper, the proposed CSA is used to search for the optimal parameters (values of inductor and capacitor) of a passive filter in the diode full-bridge rectifier. Simulation results demonstrate that the CSA-based approach can acquire the optimal LC parameters with certain given criteria for power filter design.