of an Engine Controller by means of a Genetic Algorithm using History of Search
Yasuhito Sano, Hajime Kita, I. Kamihira, Masashi Yamaguchi · 2000
In the present paper, online optimiza tion of an engine controller by means of Genetic Algorithms (GA) is discussed. In optimization of real complex systems through experiments and computer simulation using randolll variables, op timization methods must cope with uncertainty of objective function and limitation of possible number of evaluation. Sano et a1. have pro posed a GA utilizing history of search (GA with Memory-based Fitness Evaluation: MFEGA)(l) so as to reduce number of fitness evaluation for such applications of GA. In the proposed method, value of fitness function at a novel search point is estimated not only by the sampled fitness value at that point but also by utilizing the fitness val ues of individuals stored in the history of search. In the present paper, this method is applied to online optimization of an engine controller for ve hicles. Computer experiments using an engine simulator show that the proposed method out performs conventional GAs both in convergence speed and accuracy of solution under fluctu ation of fitness evaluation.