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

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

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
• Electronic ISSN: 2041-3041
• 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