An off-line approach for output feedback robust model predictive control. Issue 17 (November 2021)

• Record Type: Journal Article
• Authors: Ping, Xubin; Wang, Xiaojuan; Lin, Tingyu; Ding, Baocang; Polyakov, Andrey
• Is Part Of: Journal of the Franklin Institute. Volume 358:Issue 17(2021)
• Page Start: 9263
• Page End: 9287
• Publication Date: 2021-11
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2021.09.006
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: For constrained linear parameter varying systems subject to bounded disturbances and noises, this article investigates an off-line output feedback robust model predictive control approach. The sub-observer gains with robust positively invariant sets, and sub-controller gains with robust control invariant sets are simultaneously off-line optimized and stored in a look-up table. According to real-time estimation error bounds and estimated states, the time-varying sub-observer gains and sub-controller gains are on-line searched. The proposed off-line output feedback robust model predictive control approach with the guarantee of nested robust positively invariant sets and robust control invariant sets in theory reduces the on-line computational burden.