Control of a nonholonomic mobile robot using neural networks

Abstract

A control structure that makes possible the integration of a kinematic controller and a neural network (NN) computed-torque controller for nonholonomic mobile robots is presented. A combined kinematic/torque control law is developed using backstepping and stability is guaranteed by Lyapunov theory. This control algorithm can be applied to the three basic nonholonomic navigation problems: tracking a reference trajectory, path following and stabilization about a desired posture. Moreover, the NN controller proposed in this work can deal with unmodelled bounded disturbances and/or unstructured unmodelled dynamics in the vehicle.