Adaptive Controller Using Genetic Algorithm for Autonomous Wheeled Mobile Robot

This paper presents the application of a genetic algorithm (GA) to the problem of tracking and stabilizing the motion of a wheeled mobile robot (WMR) operating under variable conditions. The proposed approach is to apply GA to adaptive control. Its novelty is the transformation of the parameter adaptation law into an iterative form, which allows the application of GA in real time. In addition, by introducing a supervisory control into the control signal, the asymptotic stability of the closed-loop control system can be obtained. This is confirmed by the simulation carried out, which indicates that the control system achieves a high degree of motion accuracy under varying operating conditions.