Tube-based nonlinear model predictive control for autonomous skid-steer mobile robots with tire-terrain interactions
Abstract
This work addresses the problem of robust tracking control for skid-steer mobile platforms, using tube-based Nonlinear Model Predictive Control. The strategy seeks to mitigate the impact of disturbances propagated to autonomous vehicles originated by traction losses. To this end, a dynamical model composed by two coupled sub-systems stands for lateral and longitudinal vehicle dynamics and fire behavior. The controller is aimed at tracking prescribed stable operation points of the slip and side-slip beyond the robot pose and speeds. To reach robust tracking performance on the global system, a centralized control scheme operates under a predictive control framework composed by three control actions. The first one compensates for disturbances using the reference trajectory-feedforward control. The second control action corrects the errors generated by the modeling mismatch. The third one is devoted to ensure robustness on the closed-loop system whilst compensating for deviations of the state trajectories from the nominal ones (i.e. disturbance-free). The strategy ensures robust feasibility even when tightening constraints are met. Such constraints are calculated on-line based on robust positively invariant sets characterized by polytopic sets (tubes), including a terminal region to guarantee robustness. The benefits of the controller regarding tracking performance, constraint satisfaction and computational practicability were tested through simulations with a Cat (R) 262C skid-steer model. Then, in field tests, the controller evidenced high tracking accuracy against terrain disturbances when benchmarking performance with respect to inherent robust predictive controllers.
Más información
Título según WOS: | Tube-based nonlinear model predictive control for autonomous skid-steer mobile robots with tire-terrain interactions |
Título de la Revista: | CONTROL ENGINEERING PRACTICE |
Volumen: | 101 |
Editorial: | PERGAMON-ELSEVIER SCIENCE LTD |
Fecha de publicación: | 2020 |
DOI: |
10.1016/j.conengprac.2020.104451 |
Notas: | ISI |