Generalized Norm Optimal Iterative Learning Control: Constraint Handling. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Chen, Yiyang; Chu, Bing; Freeman, Christopher T.
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 13396
• Page End: 13401
• Publication Date: 2017-07
• Subjects: iterative learning control -- constraint handling; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.2275
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper proposes a novel control methodology to incorporate constraint handling within generalized iterative learning control (ILC), an overarching methodology which includes intermediate point and sub-interval tracking as special cases. The constrained generalized ILC design objective is first described, and then the design problem is formulated into a successive projection framework. This framework yields a constrained generalized ILC algorithm which embeds system input and output constraints. Convergence analysis of the algorithm is performed and supported by rigorous proofs. The algorithm is verified using a gantry robot experimental platform, whose results reveal its practical efficacy and robustness against plant uncertainty.