Abstract
In a distributed 'networked control system' (NCS), multiple physical systems or agents are connected to their corresponding controllers through a shared packet-switched communication network. For such distributed NCS, periodic sampled controller design is unsuitable to handle packet-switched closed-loop control systems, and a novel stochastic optimal adaptive event-sampled controller scheme is proposed in the application layer for each physical system or agent expressed as an uncertain linear dynamic system. Lyapunov stability analysis will be utilized to derive the event trigger condition. In addition, a network scheduling protocol is also required for such NCS. Traditional network scheduling protocols are unsuitable for such NCS since the behavior of the physical systems is disregarded during the protocol design. Therefore, in this study, a novel distributed network scheduling protocol via cross-layer approach is developed to improve the performance of distributed NCS by minimizing an overall system cost function which consists of the information collected from both the event-triggered controller for each physical system in the application layer and the distributed scheduling protocol from the network layer. It will be demonstrated that the proposed co-design approach will not only allocate the network resources efficiently but also it will improve the performance of the overall distributed NCS. Simulation results are included to demonstrate the effectiveness of the proposed cross-layer co-design.
Recommended Citation
H. Xu et al., "Stochastic Adaptive Event-triggered Control and Network Scheduling Protocol Co-design for Distributed Networked Systems," IET Control Theory and Applications, vol. 8, no. 18, pp. 2253 - 2265, Wiley Open Access; Institution of Engineering and Technology (IET), Dec 2014.
The definitive version is available at https://doi.org/10.1049/iet-cta.2014.0330
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Publication Status
Free Access
International Standard Serial Number (ISSN)
1751-8652; 1751-8644
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
11 Dec 2014
