On accommodating the semantic-based interpretability in evolutionary linguistic fuzzy controller

In this paper, we propose the accommodation of the semantic-based interpretability in evolutionary linguistic fuzzy controller through an overlap-based encoding strategy for the triangular membership function (MF) parameters. With this strategy, the coverage and the distinguishability aspect of the fuzzy partitions are guaranteed during the evolution. The idea behind this proposal is that the set of the membership functions forming the fuzzy partition are defined as overlapped functions instead of separate functions subjected to some constraints as the most previous works do. To test the design technique, simulations were performed to optimize direct-drive DC motor fuzzy controller. Simulation results show that fuzzy partition interpretability is guaranteed and the evolved FLC exhibits high performances in slow and fast tracking, as compared with the conventional PD controller.