Robust H∞ decentralized intelligent control with new learning algorithm for robot manipulators

A novel robust H^infin decentralized intelligent control (RHDIC) strategy is proposed for the trajectory following problem of robot manipulators. The proposed system is comprised of a computed torque controller and neural robust controller with new learning algorithm. Based on Lyapunov stability theorem, it is shown that the proposed controller can guarantee stability of closed-loop systems and satisfactory tracking performances. The proposed approach indicates that computed torque control method is also valid for controlling uncertain robotic manipulators as long as compensative controller is appropriately designed.