Adaptive neural-fuzzy control of uncertain constrained multiple coordinated nonholonomic mobile manipulators

Most studies on the coordination of multiple mobile manipulators system assume exact knowledge of system kinematics and dynamics, and deal only with motion tracking control. However, actual applications may involve tasks in which multiple coordinated mobile manipulators system is required to keep contact on the contour of the constraint surface in tasks. In this paper, we consider multiple mobile manipulators grasping a rigid object in contact with deformable working surfaces, whose geometric and physical model is unknown. The contact forces are nonlinear and unknown. Adaptive neuro-fuzzy (NF) control for coordinated mobile manipulators is proposed for robust force/motion tracking on the constraint surface while it is in motion. The control law is decoupled in three subspaces and adaptive tuning mechanism is developed to deal with the uncertain environmental constraints, disturbances, and unknown robotic dynamics. The proposed adaptive NF hybrid force/motion controller guarantees robust tracking of the desired motion and force trajectories. Simulation examples are presented to illustrate the results.