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Improved small gain conditions for input-to-state stability with respect to measurement functions: Discrete time networked system
Conference proceeding

Improved small gain conditions for input-to-state stability with respect to measurement functions: Discrete time networked system

Yuanqiu Mo, Changbin Yu and Soura Dasgupta
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings
12/14/2021
DOI: 10.1109/CDC45484.2021.9683129

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Abstract

Conference Title: 2021 60th IEEE Conference on Decision and Control (CDC) Conference Start Date: 2021, Dec. 14 Conference End Date: 2021, Dec. 17 Conference Location: Austin, TX, USAIn this paper we study input-to-state stability with respect to measurement functions for discrete time networked systems. In such a networked system, the trajectory of each subsystem is affected by another in each time step, and this constraining system may change from step to step. We derive small gain conditions of input-to-state stability with respect to measurement functions for this type of discrete time networked system relying on the construction of dissipative-form finite time Lyapunov function. These conditions loosen those presented in [1] and [2]. Finally, we demonstrate the applicability of our results by applying them to the stability analysis of a distributed graph algorithm which does not satisfy the conditions of [1] and [2].
Algorithms Discrete time systems Energy dissipation Liapunov functions Stability analysis Subsystems

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