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Preferences in Evolutionary Multi-Objective Optimisation with Noisy Fitness Functions : Hardware in the Loop Study

Multi-objective optimisation (MOO) is an important class of problem in engineering. The conflict of objectives in MOO places the issue of compromise in a central position. Since no single solution optimises all objectives, decision-making based on human preference is a part in solving MOO problems. In this paper application of the evolutionary MOO to the dynamic system controller design by use of the hardware in the loop is presented. Thanks to this approach problems of un-modelled plant dynamics and uncertainty of parameters are alleviated because no mathematical model is needed. The a-priori search of one solution does not require knowledge of a whole Pareto front.