<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents an approach to fault tolerant control based on the sensor masking principle in the case of wireless networked control systems. With wireless transmission, packet losses act as sensor faults. In the presence of such faults, the faulty measurements corrupt directly the behaviour of closed-loop systems. Since the controller aims at cancelling the error between the measurement and its reference input, the real outputs will, in such a networked control system, deviate from the desired value and may drive the system to its physical limitations or even to instability. The proposed method facilitates fault compensation based on an interacting multiple model approach developed in the framework of channel errors or network congestion equivalent to multiple sensors failures. The interacting multiple model method involved in a networked control system provides simultaneously detection and isolation of on-line packet losses, and also performs a suitable state estimation. Based on particular knowledge of packet losses, sensor fault-tolerant controls are obtained by computing a new control law using fault-free estimation of the faulty element to avoid intermittent observations that might develop into failures and to minimize the effects on system performance and safety.</p></abstract>

This paper presents an approach to fault tolerant control based on the sensor masking principle in the case of wireless networked control systems. With wireless transmission, packet losses act as sensor faults. In the presence of such faults, the faulty measurements corrupt directly the behaviour of closed-loop systems. Since the controller aims at cancelling the error between the measurement and its reference input, the real outputs will, in such a networked control system, deviate from the desired value and may drive the system to its physical limitations or even to instability. The proposed method facilitates fault compensation based on an interacting multiple model approach developed in the framework of channel errors or network congestion equivalent to multiple sensors failures. The interacting multiple model method involved in a networked control system provides simultaneously detection and isolation of on-line packet losses, and also performs a suitable state estimation. Based on particular knowledge of packet losses, sensor fault-tolerant controls are obtained by computing a new control law using fault-free estimation of the faulty element to avoid intermittent observations that might develop into failures and to minimize the effects on system performance and safety.

Fault tolerance in networked control systems under intermittent observations

Nancy Research Centre for Automatic Control, Nancy University, CNRS, B.P. 70239 F-54506 Vandœuvre les Nancy, France

Automatic Control, Computer Science and Signal Processing Laboratory, LAGIS FRE CNRS 3303 Polytech'Lille, Bât. D, 59655 Villeneuve d'Ascq Cedex, France

International Journal of Applied Mathematics and Computer Science

{"article-title":"Fault tolerance in networked control systems under intermittent observations"}

This paper presents an approach to fault tolerant control based on the sensor masking principle in the case of wireless networked control systems. With...

Fault tolerance in networked control systems under intermittent observations

Published Online: Dec 21, 2011

Page range: 639 - 648

DOI: https://doi.org/10.2478/v10006-011-0050-x

Keywords
network congestion, fault-tolerant control, fault diagnosis, networked control system, interacting multiple model

This content is open access.

Fault tolerance in networked control systems under intermittent observations

Published Online: Dec 21, 2011

Page range: 639 - 648

DOI: https://doi.org/10.2478/v10006-011-0050-x

Keywordsnetwork congestion, fault-tolerant control, fault diagnosis, networked control system, interacting multiple model

This content is open access.

Keywords
network congestion, fault-tolerant control, fault diagnosis, networked control system, interacting multiple model