On Local Design and Execution of a Distributed Input and State Estimation Architecture for Heterogeneous Sensor Networks
Abstract
In this paper, we focus on a new distributed input and state estimation architecture, where nodes of a given sensor network are allowed to have heterogeneous information roles in the sense that a subset of nodes can be active (that is, subject to observations of a process of interest) and the rest can be passive (that is, subject to no observations). Moreover, these nodes are allowed to have nonidentical sensor modalities under the common underlying assumption that they have complimentary properties distributed over the sensor network to achieve collective observability. The key feature of our framework is that it utilizes local information not only during the execution of the proposed distributed input and state estimation architecture but also in its design; that is, global stability is guaranteed once each node satisfies given local stability conditions (independent from the graph topology and neighboring information of these nodes). Several examples are provided to demonstrate the efficacy of the proposed approach.
Recommended Citation
D. Tran et al., "On Local Design and Execution of a Distributed Input and State Estimation Architecture for Heterogeneous Sensor Networks," Proceedings of the 2017 American Control Conference (2017, Seattle, WA), pp. 3874 - 3879, Institute of Electrical and Electronics Engineers (IEEE), May 2017.
The definitive version is available at https://doi.org/10.23919/ACC.2017.7963548
Meeting Name
2017 American Control Conference, ACC (2017: May 24-26, Seattle, WA)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Network architecture; Sensor networks; State estimation; Topology; Global stability; Graph topology; Heterogeneous information; Heterogeneous sensor networks; Local information; Local stability; Neighboring information; Sensor modality; Sensor nodes
International Standard Book Number (ISBN)
978-1-5090-5992-8
International Standard Serial Number (ISSN)
0743-1619; 2378-5861
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 May 2017