Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations
This paper covers model-based fault detection and isolation for linear and nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor and state fault detection and isolation for a class of DPS represented by a set of coupled linear partial differential equations...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10105918/ |
| _version_ | 1827949790515691520 |
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| author | Hasan Ferdowsi Jia Cai Sarangapani Jagannathan |
| author_facet | Hasan Ferdowsi Jia Cai Sarangapani Jagannathan |
| author_sort | Hasan Ferdowsi |
| collection | DOAJ |
| description | This paper covers model-based fault detection and isolation for linear and nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor and state fault detection and isolation for a class of DPS represented by a set of coupled linear partial differential equations (PDE). A filter based observer is designed based on the linear PDE representation using which a detection residual is generated. A fault is detected when the magnitude of the detection residual exceeds a detection threshold. Upon detection, several isolation estimators are designed using filters whose output residuals are compared with predefined isolation thresholds. A fault on a linear DPS is declared to be of certain type if the corresponding isolation estimator output residual is below its isolation threshold while the other fault isolation estimator output residual is above its threshold. Next, the fault location is determined when a state fault is identified. The second part of this paper focuses on fault detection and isolation of nonlinear DPS by using a Luenberger type observer. Here fault isolation framework is introduced to isolate actuator, sensor and state faults with isolability condition by using additional boundary measurements and without filters. Finally, the effectiveness of the proposed fault detection and isolation schemes for both linear and nonlinear DPS are demonstrated through simulation. |
| first_indexed | 2024-04-09T13:15:30Z |
| format | Article |
| id | doaj.art-50ead9ccec78431ab881892505d4ef74 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T13:15:30Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-50ead9ccec78431ab881892505d4ef742023-05-11T23:00:57ZengIEEEIEEE Access2169-35362023-01-0111450114502710.1109/ACCESS.2023.326870210105918Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential EquationsHasan Ferdowsi0https://orcid.org/0000-0003-2304-3399Jia Cai1Sarangapani Jagannathan2Department of Electrical Engineering, Northern Illinois University, DeKalb, IL, USAMicrosoft Corporation, Redmond, WA, USADepartment of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USAThis paper covers model-based fault detection and isolation for linear and nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor and state fault detection and isolation for a class of DPS represented by a set of coupled linear partial differential equations (PDE). A filter based observer is designed based on the linear PDE representation using which a detection residual is generated. A fault is detected when the magnitude of the detection residual exceeds a detection threshold. Upon detection, several isolation estimators are designed using filters whose output residuals are compared with predefined isolation thresholds. A fault on a linear DPS is declared to be of certain type if the corresponding isolation estimator output residual is below its isolation threshold while the other fault isolation estimator output residual is above its threshold. Next, the fault location is determined when a state fault is identified. The second part of this paper focuses on fault detection and isolation of nonlinear DPS by using a Luenberger type observer. Here fault isolation framework is introduced to isolate actuator, sensor and state faults with isolability condition by using additional boundary measurements and without filters. Finally, the effectiveness of the proposed fault detection and isolation schemes for both linear and nonlinear DPS are demonstrated through simulation.https://ieeexplore.ieee.org/document/10105918/Fault detectionfault isolationdistributed parameter systemspartial differential equations |
| spellingShingle | Hasan Ferdowsi Jia Cai Sarangapani Jagannathan Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations IEEE Access Fault detection fault isolation distributed parameter systems partial differential equations |
| title | Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations |
| title_full | Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations |
| title_fullStr | Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations |
| title_full_unstemmed | Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations |
| title_short | Filter-Based Fault Detection and Isolation in Distributed Parameter Systems Modeled by Parabolic Partial Differential Equations |
| title_sort | filter based fault detection and isolation in distributed parameter systems modeled by parabolic partial differential equations |
| topic | Fault detection fault isolation distributed parameter systems partial differential equations |
| url | https://ieeexplore.ieee.org/document/10105918/ |
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