Tube-based nonlinear model pbkp_redictive 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 Pbkp_redictive 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 tire 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 pbkp_redictive 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® 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 pbkp_redictive controllers.

Año de publicación:

2020

Keywords:

  • Autonomous industrial machinery
  • Tire slip dynamics
  • Robust pbkp_redictive control
  • Trajectory tracking
  • tire–terrain interaction

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Robótica
  • Ingeniería mecánica

Áreas temáticas:

  • Ciencias de la computación