Decision-making in fuzzy environments using ontological control with fuzzy automata

Decision-making is a process of thought. Goals and constrains in decision-making process are often treated theoretically as crisp sets. However, much of the decision-making in the real world takes place in an environment in which goals, as well as constraints and consequence of decision are not known precisely. In dealing with such sort of realistic problem, Zadeh and Bellman introduced a concept that maximizes the decision-making in fuzzy environment. Ontological control is a control methodology that deals with situations in which violation of ontological assumptions makes a programmable logic controller stay in an infinite repeating cycle. Ontological control with fuzzy automata has been introduced by Grantner to break the repeating cycle, and resume the control process. In this work, we review the basic concepts related to decision-making in fuzzy environments, then consider ontological control for system of systems (SoS) engineering applications, and use ModelSim to simulate such a process.