Extended state observer based adaptive iterative trajectory tracking control of a two-jointed robotic arm

In order to minimize the effects of inner ambiguity and outer disturbance of the robotic arm model on the controlled system and to enhance the iterative performance, the paper designs an adaptive iterative control (AILC) method with forgetting factor based on the compensation of extended state observer (ESO). This iterative algorithm for controlling the torque is designed by establishing a dynamic model of a two-jointed robotic arm, and proof of the stability and convergence of the system is given theoretically by using the composite energy function based on Lyapunov function, and the efficacy of the algorithm in this paper is demonstrated by simulations and comparison.