Abstract
The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.
Recommended Citation
A. Albattat et al., "On Event-triggered Adaptive Architectures for Decentralized and Distributed Control of Large-scale Modular Systems," Sensors (Switzerland), vol. 16, no. 8, article no. 1297, MDPI, Aug 2016.
The definitive version is available at https://doi.org/10.3390/s16081297
Department(s)
Mechanical and Aerospace Engineering
Publication Status
Open Access
Keywords and Phrases
Decentralized control; Distributed control; Event-triggered control; Large-scale modular systems; Networked control systems; System stability and performance; Uncertain dynamical systems
International Standard Serial Number (ISSN)
1424-8220
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2024 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
16 Aug 2016
