Design of switching circuits based on particle swarm optimizer and hybrid fitness function

This paper studies application of the particle swarm optimizer to finding suitable parameters for multi-objective problems in design of switching circuits. The problem is described by the hybrid fitness function consisting of analog objective functions of the parameters, criterion and digital logic. The hybrid fitness function permits increase of some fitness component(s) below the criterion and this flexibility can realize good performance. We then consider an example: optimization of switching angles of the inverters. In this application, each particle corresponds to switching angles of the inverters and moves to improve the total harmonic distortion and average power. Performing basic numerical experiments, the algorithm efficiency is confirmed.

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