Chaojiong Huang, Umar Farooq, Haiying Liu, Jason Gu, and Jun Luo
Fuzzy logic system, particle swarm optimization, mobile robot, position tracking, parameter tuning
In this paper, we proposed a simple but practical fuzzy logic position tracking controller for a wheeled mobile robot. Certain mobile robot with symmetric or ignorable body shape may focus on its position precision on a path tracking task. In this case, we assigned its position errors as input of our fuzzy logic controller and its linear and angular velocities as outputs. Then, we optimized it by tuning the parameters of scaling and membership functions using a particle swarm optimization. Our fuzzy logic system was optimized and simulated in Matlab and Simulink and was experimentally tested on Quanser’s Qbot2 robot with Quarc control system. After optimization, the values of Fitness Function (cumulative position errors) have distinctly decreased from 35.9642 to 5.8246 in simulation and from 37.4041 to 7.3935 experimentally. These results had shown that the optimized system outperformed the same system without optimization.
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