Switch-Based Iterative Learning Control for Tracking Iteration Varying References⁎This work was funded in part by NSF 1544678 and NIST Award No. 70NANB19H090. Issue 2 (2020)

• Record Type: Journal Article
• Authors: Balta, Efe C.; Tilbury, Dawn M.; Barton, Kira
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 1493
• Page End: 1498
• Publication Date: 2020
• Subjects: Repetitive systems -- iterative learning control (ILC) -- learning-based control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.1940
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Iterative Learning Control (ILC) is a control strategy that improves the performance of repetitive systems by enabling near-perfect reference tracking. Iteration-invariant reference signals have been a fundamental assumption for most existing ILC developments. This assumption poses limitations on many applications of ILC where the iteration-varying reference is known to the controller a priori. This work presents a switch-based ILC scheme that combines the performance of standard ILC with guarantees on the error for switched reference signals. The proposed controller is formulated and its performance is analyzed. A simulation case study is provided at the end to illustrate the performance.