A method of designing a family of robust compensators for a single-input/single-output linear system is presented. Each compensator’s transfer function is found by using a genetic-algorithm search for numerator and denominator coefficients. The search minimizes the probabilities of unsatisfactory stability and performance subject to real parameter variations of the plant. As the search progresses, probabilities are estimated by Monte Carlo evaluation. The design procedure employs a sweep from the lowest feasible transfer-function order to higher order, terminating either when design goals have been achieved or when no further improvement in robustness is evident. The method provides a means for estimating the best possible compensation of a given order based on repeated searches.

Issue Section:
Technical Papers
Keywords:
robust control, compensation, search problems, control system synthesis, reduced order systems, transfer functions, Monte Carlo methods, linear systems, Stochastic Robustness, Monte Carlo Evaluation, Genetic Algorithm, Weibull Distribution
Topics:
Design, Genetic algorithms, Linear systems, Probability, Robustness, Stability, Transfer functions, Weibull distribution, Robust control
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