An adaptive PID learning controller for periodic robot motion

We propose an adaptive PID learning controller which combines an adaptive PID feedback control scheme and a feedforward input learning design for the case of a periodic robot motion. The adaptive PID controller can overcome the transient response of the robot dynamics while the feedforward learning controller stands for computing the desired actuator torque needed for the nonlinear dynamics compensation in steady state. All the error signals that could appear in the learning control system are bounded, and the robot motion trajectory converges to the desired one asymptotically. On the other hand, the developed adaptive PID learning controller is compared with the fixed PID learning controller from the stability point of view to assure the gain bound, performance of tracking and, the most important, the convergence rate of the learning system.