Control of a nonholonomic mobile robot using neural networks

Authors:
R. Fierro;F. L. Lewis
Affiliations:
Fac. de Ingenieria Electr., Escuela Politecnica Nacional, Quito;-
Venue:
IEEE Transactions on Neural Networks
Year:
1998

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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 unmodeled bounded disturbances and/or unstructured unmodeled dynamics in the vehicle. Online NN weight tuning algorithms do not require off-line learning yet guarantee small tracking errors and bounded control signals are utilized