An improved trajectory tracking decentralized adaptive controller for robot manipulators

A decentralized adaptive nonlinear controller for a robot manipulator is presented in this paper. Based on the promising results obtained by the decentralized adaptive PID control algorithms proposed by Seraji and other researchers, the authors redesigned the Lyapunov function, and as a result, achieved a further simplification of the control algorithm and better trajectory tracking performance. The main advantages of the proposed controller over similar controllers are the considerably faster convergence of tracking error, relatively simpler structure, and smoother control activity. Another advantage of this controller is that it only requires local position and velocity measurements, and it does not make use of the exact centralized mathematical model of the robot manipulator. Finally, the authors demonstrate through computer simulation the robustness of their controller against parameter variations and disturbances