Evolutionary Algorithms for Automatic Tuning of QFT Controllers

M. García-Sanz and J.A. Osés (Spain)


QFT Control, Multi-objective Optimization, EvolutionaryAlgorithms.


Controller synthesis with QFT (Quantitative Feedback Theory) sometimes requires an important designer effort, usually done manually. In this context, automation of the loop-shaping stage can highly improve the productivity of the methodology. This paper explores the possibilities that offer evolutionary algorithms for automatic tuning of QFT controllers. A simple evolutionary algorithm based on evolution strategies and genetic algorithms is introduced. The synthesis problem is defined in terms of a multi objective optimization with constraints. The paper finishes with a benchmark example to analyse and validate the new algorithm for automatic tuning.

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