Genetic algorithms for control of power converters

This paper evaluates genetic algorithms (GAs) as a new nonlinear technique for the control of power converters. Genetic algorithms are a class of parallel processing learning techniques. They are used to optimize power converter control laws relative to a performance index. An example using a full-bridge topology verifies the usefulness of this technique.<
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