Distributed fault diagnosis of networked dynamical systems with time-varying topology. Issue 11 (July 2019)

• Record Type: Journal Article
• Authors: Peng, Chen; Zhou, Yanlin; Hui, Qing
• Is Part Of: Journal of the Franklin Institute. Volume 356:Issue 11(2019)
• Page Start: 5754
• Page End: 5780
• Publication Date: 2019-07
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2019.05.027
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: In this paper, the distributed fault diagnosis (DFD) of networked dynamical systems with time-varying connected topologies, e.g., wireless sensor networks in harsh environments, is considered. Specifically, two essential problems are focused on, which are faced in extending the the decomposition-based adaptive DFD approach to such topology-varying systems. The problems introduced by the time-varying topologies are, respectively, decomposition schemes deterioration and pre-training difficulties. The causes of the two problems are detailed and addressed in our work. First, for the decomposition schemes deterioration problem, a multi-agent dynamics-based online distributed decomposition algorithm are developed, so that a decent decomposed network structure for such topology-varying network can be maintained. Second, to alleviate the pre-training difficulties in topology-varying systems, a fault detection method is proposed, which avoids the need for pre-training. The distributed decomposition algorithm is proved to converge in finite steps, and the proposed fault detection method is verified both theoretically and experimentally.