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An evolutionary approach for probabilistic temporal fuzzy controllers

Temporal fuzzy systems are powerful systems that use temporal information in their reasoning process. Probabilistic fuzzy systems are the systems that combine the advantages of probabilistic and fuzzy uncertainty with each other. In this paper, we propose a novel approach, which combines the advantages of probabilistic fuzzy systems with temporal fuzzy systems. The proposed algorithm uses an evolutionary algorithm to find the parameters of the system. In order to examine the proposed method, a fuzzy controller for an overhead crane system is designed. Simulation results show that the proposed method has better performance than other methods.