Adaptive PID learning of periodic robot motion

Abstract

An adaptive PID learning controller which consists of an adaptive PID feedback control scheme and a feedforward input learning scheme is proposed for learning of periodic robot motion. In the learning controller, the adaptive PID feedback controller takes part in stabilizing the transient response of robot dynamics while the feedforward learning controller plays a role in computing the desired actuator torques for feedforward nonlinear dynamics compensation in steady state. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. In addition, the proposed adaptive PID learning controller is compared with the fixed PID learning controller in terms of the stability condition of lower PID gain bound, the performance of tracking, and the convergence rate of desired learning input.