Sparse iterative learning control with application to a wafer stage: Achieving performance, resource efficiency, and task flexibility

作者：Oomen Tom^*; Rojas Cristian R

来源：Mechatronics, 2017, 47: 134-147.

DOI：10.1016/j.mechatronics.2017.09.004

• Iterative learning control
• Motion control
• Feedforward
• Sparse optimization
• Resource-efficient control

Trial-varying disturbances are a key concern in Iterative Learning Control (ILC) and may lead to inefficient and expensive implementations and severe performance deterioration. The aim of this paper is to develop a general framework for optimization-based ILC that allows for enforcing additional structure, including sparsity. The proposed method enforces sparsity in a generalized setting through convex relaxations using el norms. The proposed ILC framework is applied to the optimization of sampling sequences for resource efficient implementation, trial-varying disturbance attenuation, and basis function selection. The framework has a large potential in control applications such as mechatronics, as is confirmed through an application on a wafer stage.

• 出版日期2017-11