This paper presents an evolutionary methodology to automatically generate nite state automata (FSA) controllers to control hybrid systems. FSA controllers for a case study of two-tank system have been successfully obtained using the proposed evolutionary approach. Experimental results show that these controllers have good performance on the set of training targets as well as on a randomly generated set of validation targets.
2009 World Summit on Genetic and Evolutionary Computation, 2009 Gec Summit - Proceedings of the 1st Acm/sigevo Summit on Genetic and Evolutionary Computation, Gec'09, 2009, p. 105-111
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World Summit on Genetic and Evolutionary Computation, 2009