Automatic loop-shaping of QFT robust controllers

This paper introduces a methodology to design automatically QFT (Quantitative Feedback Theory) robust controllers for SISO (single input-single output) plants with model uncertainty. The method generalizes previous automatic loop-shaping techniques, avoiding restrictive assumptions about the search space. This methodology applies two strategies: a) Evolutionary Algorithms, and b) Genetic Algorithms (GA). In both cases the objective is to search the QFT robust controller that fulfils the control specifications for the whole set of plant models within the uncertainty. Each strategy has been applied to a benchmark in order to validate the techniques.

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