This paper proposes a novel fault isolation (FI) scheme for distributed parameter
systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear
uncertain dynamics. A key feature of the proposed FI scheme is its capability of dealing with the
effects of system uncertainties for accurate FI. Specifically, an approximate ordinary differential
equation (ODE) system is first derived to capture the dominant dynamics of the original
PDE system. An adaptive dynamics identification approach using radial basis function neural
network is then proposed based on this ODE system, to achieve locally-accurate identification
of the uncertain system dynamics under faulty modes. A bank of FI estimators with associated
adaptive thresholds are finally designed for real-time FI decision making. Rigorous analysis
on the fault isolatability is provided. Simulation study on a representative transport-reaction
process is conducted to demonstrate the effectiveness of the proposed approach.
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Fault Detection and Isolation of Uncertain Nonlinear Parabolic PDE Systems
This paper proposes a novel fault detection and isolation (FDI) scheme for distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear uncertain dynamics. A key feature of the proposed FDI scheme is its capability of dealing with the effects of system uncertainties for accurate FDI. Specifically, an approximate ordinary differential equation (ODE) system is first derived to capture the dominant dynamics of the original PDE system. An adaptive dynamics identification approach using radial basis function neural network is then proposed based on this ODE system, so as to achieve locally-accurate identification of the uncertain system dynamics under normal and faulty modes. A bank of FDI estimators with associated adaptive thresholds are finally designed for real-time FDI decision making. Rigorous analysis on the FDI performance in terms of fault detectability and isolatability is provided. Simulation study on a representative transport-reaction process is conducted to demonstrate the effectiveness and advantage of the proposed approach.
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- Award ID(s):
- 1929729
- NSF-PAR ID:
- 10345143
- Date Published:
- Journal Name:
- ArXivorg
- ISSN:
- 2331-8422
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/https://doi.org/10.48550/arXiv.2203.15850
