Fast-Update Iterative Learning Control for Performance Enhancement With Application to Motion Systems

Abstract

Iterative learning control (ILC) algorithms are typically used to improve the performance of repetitive processes. Numerous successful applications of ILC, such as computer numerical control (CNC) machining processes, robot manipulation, and lithography processes, have been reported. However, ILC often exhibits less than satisfactory performance since the control unit operates at a limited sampling rate in consideration of cost. In this study, the multiloop, multirate structure of servo motor control systems is taken advantage of and a fast-update multirate ILC (FILC) scheme is proposed for high-accuracy trajectory tracking, where compensation is updated at a rate faster than that of the original position loop without the need for redesigning the feedback controller. The key difficulty related to the design of the FILC lies in the extremely complex and time-varying dynamics inherent in multirate systems. To address this problem, a novel equivalent single-rate parametric model description of the multirate system is derived, which enables the use of the efficient norm optimal ILC algorithm. Consequently, a computationally efficient FILC is obtained to improve the performance. Subsequently, the proposed FILC is applied to the position control of the CNC motion stage. Simulation and experimental results are used to verify the effectiveness of the proposed method.INDEX TERMS Iterative learning control, multirate system, norm optimal, linear peridoic time varying, precise motion control

Multivariable Iterative Learning Control Design for Precision Control of Flexible Feed Drives

“…Furthermore, feedforward friction compensation is effectively implemented by a look-up table, which is based on the result gathered from preliminary friction identified experiments. To prevent instantaneous In this framework, C P (z) denotes the position loop feedback controller, C v (z) denotes the velocity feedback controller, and C i (z) encapsulates the combination of the current loop controller and its corresponding filter [2]. The position loop controller is configured as a proportional (P) controller, and the velocity controller is designed as a proportional-integral (PI) controller.…”

“…In this framework, denotes the position loop feedback controller, denotes the velocity feedback controller, and encapsulates the combination of the current loop controller and its corresponding filter [ 2 ]. The position loop controller is configured as a proportional ( ) controller, and the velocity controller is designed as a proportional-integral ( ) controller.…”

“…In advanced manufacturing equipment such as manipulators [ 1 ], CNC machine tools [ 2 ], 3D printers [ 3 ], and lithography machines [ 4 ], the throughput and accuracy of workpieces are significantly affected by the dynamic positioning accuracy of their feed drive systems. In industrial applications, electromechanical systems are inevitably affected by the structural dynamics of the feed drives and uncertain disturbance, significantly limiting the achievable accuracy of motion control systems.…”