Evolutionary Design of Fuzzy Logic Based Position Controller for Mobile Robot

This paper develops a fuzzy logic based position controller whose membership functions are tuned by genetic algorithm. The main goal is to ensure successful velocity and position trajectories tracking between the mobile robot and the virtual reference cart. The proposed fuzzy controller has two inputs and two outputs. The first input represents the distance between the mobile robot and the reference cart. The second input is the angle formed by the straight line defined with the orientation of the robot, and the straight line that connects the robot with the reference cart. The outputs represent linear and angular velocity commands, respectively. The performance of the fuzzy controller is validated through comparison with previously developed mobile robot position controller based on control Lyapunov functions (CLF). Simulation results indicate good performance of position tracking while at the same time a substantial reduction of the control torques is achieved.