Point stabilization of mobile robots by genetic sliding mode approach with neural dynamics model on uneven surface

In this work, a novel point stabilization control strategy for mobile robots which moves on uneven surface is presented. Firstly, sliding mode method is adopted to extend the nonlinear kenimatic control law to dynamic system, so that the robot is driven by torques. Then, to solve the speed and torque jump problem, the neural dynamics model is integrated into the presented controller. In addition, we utilize genetic algorithm (GA) to optimize the controller parameters for obtaining better stabilization performance. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, simulation results are given to illustrate the effectiveness of the proposed control scheme.