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An interaction predictive approach to fault-tolerant control in network control systems

Patton, RJ; Kambhampati, C; Perkgoz, C; Patton, R. J.; Ahamed, W

Authors

RJ Patton

C Perkgoz

Profile image of Ron Patton

Professor Ron Patton R.J.Patton@hull.ac.uk
Emeritus Professor of Control and Intelligent Systems Engineering

W Ahamed



Abstract

This paper illustrates some of the capabilities of previously proposed network control system (NCS) architectures to carry on functioning in the event of faults, without recourse to system reconfiguration. The principle of interaction prediction is used to set up a coordination strategy that encapsulates an ability to withstand or tolerate certain faults, thereby allowing the system to continue functioning. It is also shown that the coordination strategy can be made more effective if a learning agent is allowed to learn the coordination functions. This facilitates the use of different types of agent at the local level, together with recurrent networks and genetic algorithms (GAs) at the coordination level. The experimental test-bed system is a benchmark three-tank system that has some of the main features of an industrial process control system.

Citation

Kambhampati, C., Perkgoz, C., Patton, R. J., & Ahamed, W. (2007). An interaction predictive approach to fault-tolerant control in network control systems. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 221(6), 885-894. https://doi.org/10.1243/09596518jsce377

Journal Article Type Article
Acceptance Date Dec 31, 2007
Online Publication Date Sep 1, 2007
Publication Date Sep 1, 2007
Journal Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
Print ISSN 0959-6518
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 221
Issue 6
Pages 885-894
DOI https://doi.org/10.1243/09596518jsce377
Keywords Fault-tolerant control; Network control systems; Interaction prediction; Multiagents; Autonomous control
Public URL https://hull-repository.worktribe.com/output/409670
Publisher URL https://journals.sagepub.com/doi/10.1243/09596518JSCE377