A systematic design framework for iterative learning control with current feedback. (30th September 2018)

• Record Type: Journal Article
• Authors: Zheng, Minghui; Zhang, Fu; Liang, Xiao
• Is Part Of: IFAC journal of systems and control. Volume 5(2018)
• Page Start: 1
• Page End: 10
• Publication Date: 2018-09-30
• Subjects: Automatic control -- Periodicals; Relay control systems -- Periodicals; Embedded computer systems -- Periodicals; Feedback control systems -- Periodicals; Artificial intelligence -- Periodicals; Artificial intelligence; Automatic control; Embedded computer systems; Feedback control systems; Relay control systems; Electronic journals; Periodicals; 629.89
• DOI: 10.1016/j.ifacsc.2018.06.001
• Languages: English
• ISSNs: 2468-6018

Abstract

Abstract: Iterative learning control (ILC) has been a powerful control technique to improve systems' tracking performance over iterations. ILC with current feedback provides new opportunities for potential faster convergence. This paper proposes a systematic design framework for a generalized N th-order ILC with current feedback information. The ILC design problem is formulated into an H-infinity optimal control design problem for a constructed system; the convergence over iterations and the stability of the feedback loop are guaranteed simultaneously. Numerical studies are performed to illustrate the design procedure and validate various types of ILCs designed under the proposed framework.