Abstract
In this paper, fuzzy multiobjective optimal control (FMOC), which consists of fuzzy multiobjective predictive control (FMPC) and adaptive fuzzy multiobjective predictive control (AFMPC), is proposed to control complex processes with high performance. FMOC can approximately mimic the behavior of the human operator in controlling complex processes through thorough evaluation of multiple control objectives with different importances. FMOC reflects not only the multiobjectiveness of the human operator's behavior, but also the influence of his psychology on his control strategy. In this paper, intelligent multiobjective optimal control (IMOC) based on process partition, real-time expert system techniques and FMOC is briefly reviewed too. FMOC has been used to implement an intelligent automatic train control system (IATCS) and the simulation results have proved the feasibility of the approach proposed.
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