Remote Control for Robot Manipulators with Neural Network Compensation

A new remote time-delay feedback controller is presented for a class of robot manipulator systems with unknown nonlinear dynarnics and communication time-delay. The proposed control scheme consists of a local neural network (NN) compensation and a time-delay feedback controller. A NN-based identification is first employed to identify the robot manipulator system. Local linearization compensation is then used to cancel the unknown nonlinearity of the system. The filter technology is utilized to obtain the time-delay-free inverse model of the linearized system and a desired reference model is used to constitute the feedback controller, which can achieve the tracking performance. Rigorous stability analysis and simulation are both included to verify the effectiveness of the proposed scheme.