A Framework on Fully Distributed State Estimation and Cooperative Stabilization of LTI Plants

TL;DR

This paper presents a fully distributed framework for state estimation and stabilization of LTI plants in multi-agent systems, enabling nodes to cooperatively control plants over directed graphs without global information.

Contribution

It introduces a novel adaptive consensus estimator and local controllers that work under mild conditions, applicable to noise-bounded plants and purely distributed scenarios.

Findings

Estimator achieves accurate state estimation without global topology info.

Controllers guarantee plant stabilization with only strong connectivity requirement.

Framework validated through numerical examples.

Abstract

How to realize high-level autonomy of individuals is one of key technical issues to promote swarm intelligence of multi-agent (node) systems with collective tasks, while the fully distributed design is a potential way to achieve this goal. This paper works on the fully distributed state estimation and cooperative stabilization problem of linear time-invariant (LTI) plants with multiple nodes communicating over general directed graphs, and is aimed to provide a fully distributed framework for each node to perform cooperative stabilization tasks. First, by incorporating a novel adaptive law, a consensus-based estimator is designed for each node to obtain the plant state based on its local measurement and local interaction with neighbors, without using any global information of the communication topology. Subsequently, a local controller is developed for each node to stabilize the plant collaboratively with performance guaranteed under mild conditions. Specifically, the proposed method only requires that the communication graph be strongly connected, and the plant be collectively controllable and observable. Further, the proposed method can be applied to pure fully distributed state estimation scenarios and modified for noise-bounded LTI plants. Finally, two numerical examples are provided to show the effectiveness of the theoretical results.