A Bayesian Approach for Fault Diagnosis in an Irrigation Canal

Lami, Youness; Lefèvre, Laurent; Lagreze, Andre; Genon-Catalot, Denis

doi:10.1109/icstcc50638.2020.9259694

Cited by 3 publications

(1 citation statement)

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“…In [ 26 ], a fault-detection filter subject to limited transmission through a network with time-varying latency and fading was successfully designed. A Bayesian approach was used instead in [ 27 ] for NCS fault diagnosis in an irrigation canal application, while in [ 28 ] the authors used a Markov jumping linear system (MJLS) approach for the design of a residual generator. NCS robust fault-tolerant control is also an alternative, which was subsequently considered, for example, in [ 29 ]; faults were modeled as MJLSs with incomplete transition probabilities, and LMI-based sufficient conditions were then used to ensure stability.…”

Section: Introductionmentioning

confidence: 99%

Differential Entropy-Based Fault-Detection Mechanism for Power-Constrained Networked Control Systems

Rojas

2024

Entropy

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In this work, we consider the design of power-constrained networked control systems (NCSs) and a differential entropy-based fault-detection mechanism. For the NCS design of the control loop, we consider faults in the plant gain and unstable plant pole locations, either due to natural causes or malicious intent. Since the power-constrained approach utilized in the NCS design is a stationary approach, we then discuss the finite-time approximation of the power constraints for the relevant control loop signals. The network under study is formed by two additive white Gaussian noise (AWGN) channels located on the direct and feedback paths of the closed control loop. The finite-time approximation of the controller output signal allows us to estimate its differential entropy, which is used in our proposed fault-detection mechanism. After fault detection, we propose a fault-identification mechanism that is capable of correctly discriminating faults. Finally, we discuss the extension of the contributions developed here to future research directions, such as fault recovery and control resilience.

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