Neural Network Predictive Trajectory Tracking of an Autonomous Two-Wheeled Mobile Robot
Abstract
As a prerequisite for precise trajectory tracking of a two-wheeled mobile robot, accurate control of the velocity and the curvature along a predefined trajectory is vital. After offline training, a neural network is used for nonlinear predictive control. To make the system more robust against modeling inaccuracies and other disturbance influences, the control error is integrated and used to adjust the control variables calculated by the predictor.
