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Cited by 278

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Fault-tolerant control in dynamic systems: application to a winding machine

·2000·IEEE Control Systems

Abstract

The general fault-tolerant control method described in the article addresses actuator and sensor faults, which often affect highly automated systems. These faults correspond to a loss of actuator effectiveness or fault sensor measurements. After describing these faults, a fault estimation and compensation method was proposed. In addition to providing information to operators concerning the system operating conditions, the fault diagnosis module is especially important in fault-tolerant control systems where one needs to know exactly which element is faulty to react safely. The method's abilities to compensate for such faults are illustrated by applying it to a winding machine, which represents a subsystem of many industrial systems. The results show that once the fault is detected and isolated, it is easy to reduce its effect on the system, and process control is resumed with degraded performances close to nominal ones. Thus, stopping the system immediately can be avoided. However, the limits of this method are reached when there is the complete loss of an actuator. In this case, only a hardware redundancy is effective and could ensure performance reliability. The method proposed here assumes the availability of the state variables for measurement.

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Metadata

Venue
IEEE Control Systems
Published
2000-02
Volume
20
Issue
1
Pages
33-49
ISSN
  • 1066-033X (ISSN-L)
  • 1941-000X
OpenAlex
W2013219041
Cited by
278
References
0
FWCI
32.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fault-tolerant control in dynamic systems: application to a winding machine. https://app.cochat.ai/papers/10.1109/37.823226
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Fault-tolerant control in dynamic systems: application to a winding machine. (2000). IEEE Control Systems. https://doi.org/10.1109/37.823226

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.