Analysis and experiments of iterative learning-control system with uncertain dynamics

An iterative error compensation approach is proposed in this article to improve the accuracies of high speed, computer-controlled machining processes. It is well known that the high-speed computer-numerically-controlled (CNC) machines are extremely useful in terms of manufacturing mass-produced parts. The proposed method uses an iterative learning technique that adopts the servo commands and cutting error experienced in previous maneuvers as references to current compensative actions. Moreover, non-repetitive disturbances and nonlinear dynamics of the cutting processes, and servo systems of the CNC machine that greatly affect the convergence of the learning-control systems were also studied in this research. State feedback and output feedback techniques were adopted in the proposed controller design. In addition to the stability analysis, a 1 degree-of-freedom servo positioning system is constructed to evaluate the performance of our proposed learning control approach. Both the simulation and experimental results verify the effectiveness of our approach.