Inferential Iterative Learning Control: A 2D-system approach. (September 2016)

• Record Type: Journal Article
• Authors: Bolder, Joost; Oomen, Tom
• Is Part Of: Automatica. Volume 71(2016)
• Page Start: 247
• Page End: 253
• Publication Date: 2016-09
• Subjects: Iterative Learning Control -- Inferential control -- 2D system -- Stability along the pass -- Limit profile; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2016.04.029
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: Certain control applications require that performance variables are explicitly distinguished from measured variables. The performance variables are not available for real-time feedback. Instead, they are often available after a task. This enables the application of batch-to-batch control strategies such as Iterative Learning Control (ILC) to the performance variables. The aim of this paper is first to show that the pre-existing ILC controllers may not be directly implementable in this setting, and second to develop a new approach that enables the use of different variables for feedback and batch-to-batch control. The analysis reveals that by using pre-existing ILC methods, the ILC and feedback controllers may not be stable in an inferential setting. Therefore, the complete closed-loop system is cast in a 2D framework to analyze stability. Several solution strategies are outlined. The analysis is illustrated through an application example in a printing system. Finally, the developed theory also leads to new results for traditional ILC algorithms in the common situation where the feedback controller contains a pure integrator.