Abstract
Design of optimal control system by use of a multicriteria genetic algorithm (GA) is presented. A new problem formulation and a new GA solution technique using the Pareto set concept is developed. The performance index of a linear control system is usually the time integral of the sum of quadratic forms xTQx and uTRu, where the choice of the weighting matrices Q and R are almost always heuristic in nature. Thus a re-formulation of the optimal control system design as a multicriteria optimization task is developed here which avoids use of Q and R. Design of the optimal control system is considered as a feedback search procedure where a new design solution is assigned a fitness value for the GA by a reference to the previously obtained Pareto optimal solution set. A numerical control design example and simulation results are presented.
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