2020/08/11 by Tianchen Ji, Junyi Geng, Ji, Tianchen +3
Biochemistry, Genetics and Molecular Biology · Engineering · #Advanced Control Systems Optimization #FOS: Electrical engineering #FOS: Mathematics #Fault Detection and Control Systems #Gene Regulatory Network Analysis #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2008.04980
openalex publication_date 2020/08/11 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
Robust design of autonomous systems under uncertainty is an important yet challenging problem. This work proposes a robust controller that consists of a state estimator and a tube based predictive control law. The class of linear systems under ellipsoidal uncertainty is considered. In contrast to existing approaches based on polytopic sets, the constraint tightening is directly computed from the ellipsoidal sets of disturbances without over-approximation, thus leading to less conservative bounds. Conditions to guarantee robust constraint satisfaction and robust stability are presented. Further, by avoiding the usage of Minkowski sum in set computation, the proposed approach can also scale up to high-dimensional systems. The results are illustrated by examples.