Robust Output Feedback MPC with Reduced Conservatism under Ellipsoidal Uncertainty
Robust Output Feedback MPC with Reduced Conservatism under Ellipsoidal Uncertainty
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DOI：
10.1109/cdc51059.2022.9992704
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
Tianchen Ji;Junyi Geng;Katherine Driggs Campbell
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文献类型：
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作者：
Tianchen Ji;Junyi Geng;Katherine Driggs Campbell
不确定条件下自治系统的稳健设计是一个重要而又具有挑战性的问题。本文提出了一种由状态估计器和基于管子的预测控制律组成的鲁棒控制器。考虑一类具有椭球不确定性的线性系统。与现有的基于多面体集的方法相比，约束紧缩量直接从椭球扰动集计算，没有过逼近，从而导致更少的保守界。给出了保证鲁棒约束满足和鲁棒稳定性的条件。此外，通过避免在集合计算中使用Minkowski和，该方法还可以扩展到高维系统。通过算例说明了结果的正确性。
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.