Abstract
The authors investigate the application of a genetic algorithm for optimizing the gains of a proportional-plus-integral controller for a hydrogenerator plant. The genetic algorithm was applied to optimal tuning of a governor for a hydrogenerator plant. Analog and digital simulation methods are compared for use in conjunction with the genetic algorithm optimization process. It is shown that analog plant simulation provides advantages in speed over digital plant simulation. This speed advantage makes application of the genetic algorithm in an actual plant environment feasible. The genetic algorithm is shown to possess the ability to reject plant noise and other system anomalies in its search for optimizing solutions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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