| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 699857 | Control Engineering Practice | 2011 | 8 Pages |
This paper presents an approach to adaptive trajectory tracking of mobile robots which combines a feedback linearization based on a nominal model and a RBF-NN adaptive dynamic compensation. For a robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematics controller and an inverse dynamics controller. The uncertainty in the nominal dynamics model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The analysis of the RBF-NN approximation error on the control errors is included. Finally, the performance of the control system is verified through experiments.
Research highlights►Adaptive trajectory tracking of mobile robots. ► Combines a feedback linearization based on a nominal model and a RBF-NN compensation. ► Robot with uncertain dynamic parameters, two controllers are implemented separately. ►Uncertainty in the nominal dynamics model is compensated by a RBF-NN. ►Control system performance is verified through experiments
