Adaptive NN Controller Design of Mobile Manipulators with Uncertain Dynamics

In this paper, a mobile manipulator robot comprising a mobile platform with a three-link arm mounted on top of the platform is considered, A neural network (NN)-based methodology is developed for the motion control of mobile manipulators subject to kinematic constraints. The dynamics of the mobile manipulator is assumed to be completely unknown, and is identified on-line by the NN estimators. No preliminary learning stage of NN weights is required. The controller is capable of disturbance-rejection in the presence of unmodeled bounded disturbances. The tracking stability of the closed-loop system, the convergence of the NN weight-up dating process and boundedness of NN weight estimation errors are all guaranteed. The complete base arm controller has an adaptive feedback linearization inner loop, which takes into account the non-holonomic constraints and compensates for a possibly moving on-board arm, and an outer loop for either tracking or path following, thus achieving coordinated vehicle/arm motion. The net result is a base plus arm motion controller that is capable of achieving a coordinated motion of the base plus arm in the presence of uncertain dynamics, load and the environment.

Keywords:

mobile robot , Adaptive Controller , NN Controller , non-holonomic constraints , End-effectro trajectory tracking