Robust wavelet network control for a class of autonomous vehicles to track environmental contour line

Abstract

We address the problem of environmental contour line tracking for a class of autonomous vehicles. A reference velocity is designed for the autonomous vehicles to do contour line tracking. Based on Lashall invariance principle, an ideal controller is designed for the vehicle with ideal model and ideal information about the environmental concentration function to track the desired contour line. For the vehicle with possibly modeling uncertainty, we combine a neural controller containing a wavelet neural network (WNN) identifier with a robust control to construct a robust adaptive WNN control for the vehicle to track the desired environmental contour line. Then we give theoretical proof of the efficiency of the designed robust adaptive WNN control. Simulation results and conclusion are presented and discussed.