Cross-Coupled Iterative Learning Control for Complex Systems
A Monotonically Convergent and Computationally Efficient Approach
More Info
expand_more
expand_more
Abstract
Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. The aim of this paper is to develop a framework for norm-optimal cross-coupled ILC that enables the use of exact contour errors that are calculated offline, and iteration-and time-varying weights. Conditions for the monotonic convergence of this iteration-varying ILC algorithm are developed. In addition, a resource-efficient implementation is proposed in which the ILC update law is reframed as a linear quadratic tracking problem, reducing the computational load significantly. The approach is illustrated on a simulation example.
Files
Cross_Coupled_Iterative_Learni... (.pdf)
(.pdf | 1.1 Mb)
- Embargo expired in 10-07-2023