Adaptive critic design for intelligent steering and speed control of a 2-axle vehicle

Selected adaptive critic (AC) methods are known to be capable of designing (approximately) optimal control policies for nonlinear plants. The present research focuses on an AC method known as dual heuristic programming (DHP). In particular it is seen as useful to explore correspondences between the form of a utility function and the resulting controllers designed by the DHP method. Based on the task of designing a steering controller for a 2-axle, terrestrial, autonomous vehicle, the present paper relates a pair of critics to “divide the labor” of training the controller. Improvements in convergence of the training process is realized in this way. The controllers designed by the DHP method are reasonably robust, and demonstrate good performance on disturbances not even trained on encountering a patch of ice during a steering maneuver, and encountering a wind gust perpendicular to direction of travel