A hybrid optimization algorithm in power filter design

Clonal selection algorithm (CSA) is one of the most widely employed immune-based approaches for handling optimization tasks. Characterized with the similartaxis and dissimilation properties, Mind evolutionary computation (MEC) is a new evolutionary computation method. In this paper, we propose a hybrid optimization algorithm based on the principles of the CSA and MEC 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 our algorithm can acquire the optimal LC parameters within the given criteria for power filter design.