Interval Observer Synthesis for Locally Lipschitz Nonlinear Dynamical Systems via Mixed-Monotone Decompositions
Mohammad Khajenejad, Fatima Shoaib, Sze Zheng Yong

TL;DR
This paper introduces a unified interval observer synthesis method for locally Lipschitz nonlinear systems using mixed-monotone decompositions, ensuring correctness without extra constraints and providing LMI-based stabilizing gain conditions.
Contribution
It presents a novel observer design approach that guarantees correctness by construction for nonlinear systems without requiring global Lipschitz conditions.
Findings
The proposed observer is correct by construction for locally Lipschitz systems.
Sufficient LMI conditions for stabilizing observer gains are derived.
Performance comparisons show advantages over existing observers.
Abstract
This paper proposes a novel unified interval-valued observer synthesis approach for locally Lipschitz nonlinear continuous-time (CT) and discrete-time (DT) systems with nonlinear observations. A key feature of our proposed observer, which is derived using mixed-monotone decompositions, is that it is correct by construction (i.e., the true state trajectory of the system is framed by the states of the observer) without the need for imposing additional constraints and assumptions such as global Lipschitz continuity or contraction, as is done in existing approaches in the literature. Furthermore, we derive sufficient conditions for designing stabilizing observer gains in the form of Linear Matrix Inequalities (LMIs). Finally, we compare the performance of our observer design with some benchmark CT and DT observers in the literature.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStability and Control of Uncertain Systems · Control and Stability of Dynamical Systems · Dynamics and Control of Mechanical Systems
