Abstract
This paper aims at measuring the improvement in performance and efficiency of fuzzy controllers after being optimized. The Stochastic Fractal Search (SFS) method is used to optimize the membership functions of a fuzzy controller for an autonomous mobile robot. The experimentation is based on getting the method to reduce the error that exists between the desired trajectory and the real trajectory of the robot. First, the efficiency of the SFS method is tested with benchmark functions, which aims at finding the overall minimum for each of the functions. The SFS method is inspired by fractals, a kind of fragmented structure, which grows at every scale with self-similarity. After testing with different dimensions in the Unimodal functions and Multimodal functions, we proceed with the optimization of the fuzzy controller. Simulation results show the advantages of SFS in fuzzy control optimization.
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