Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers
Quick and timely fault detection is of great importance in control systems reliability. Undetected faulty sensors could result in irreparable damages. Although fault detection and isolation (FDI) methods in control systems have received much attention in the last decade, these techniques have not be...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-04-01
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| Series: | Automatika |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/00051144.2019.1706911 |
| _version_ | 1819060661979709440 |
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| author | Farideh Allahverdi Amin Ramezani Mehdi Forouzanfar |
| author_facet | Farideh Allahverdi Amin Ramezani Mehdi Forouzanfar |
| author_sort | Farideh Allahverdi |
| collection | DOAJ |
| description | Quick and timely fault detection is of great importance in control systems reliability. Undetected faulty sensors could result in irreparable damages. Although fault detection and isolation (FDI) methods in control systems have received much attention in the last decade, these techniques have not been applied for some classes of nonlinear systems yet. This paper deals with the issues of sensor fault detection and isolation for a class of Lipschitz uncertain nonlinear system. By introducing a coordinate transformation matrix for states and output, the original system is first divided into two subsystems. The first subsystem is affected by uncertainty and disturbance. The second subsystem just has sensor faults. The nonlinear term is separated to linear and pure nonlinear parts. For fault detection, two sliding mode observers (SMO) are designed for the two subsystems. The stability condition is obtained based on the Lyapunov approach. The necessary matrices and parameters are obtained by solving the linear matrix inequality (LMI) problem. Furthermore, two sliding mode observers are designed for fault isolation. Finally, the effectiveness of the proposed approach is illustrated by simulation examples. |
| first_indexed | 2024-12-21T14:30:33Z |
| format | Article |
| id | doaj.art-dc688813da714f61aefaa4dfb1487ef9 |
| institution | Directory Open Access Journal |
| issn | 0005-1144 1848-3380 |
| language | English |
| last_indexed | 2024-12-21T14:30:33Z |
| publishDate | 2020-04-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Automatika |
| spelling | doaj.art-dc688813da714f61aefaa4dfb1487ef92022-12-21T19:00:30ZengTaylor & Francis GroupAutomatika0005-11441848-33802020-04-0161221922810.1080/00051144.2019.17069111706911Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observersFarideh Allahverdi0Amin Ramezani1Mehdi Forouzanfar2Ahvaz Branch, Islamic Azad UniversityAhvaz Branch, Islamic Azad UniversityAhvaz Branch, Islamic Azad UniversityQuick and timely fault detection is of great importance in control systems reliability. Undetected faulty sensors could result in irreparable damages. Although fault detection and isolation (FDI) methods in control systems have received much attention in the last decade, these techniques have not been applied for some classes of nonlinear systems yet. This paper deals with the issues of sensor fault detection and isolation for a class of Lipschitz uncertain nonlinear system. By introducing a coordinate transformation matrix for states and output, the original system is first divided into two subsystems. The first subsystem is affected by uncertainty and disturbance. The second subsystem just has sensor faults. The nonlinear term is separated to linear and pure nonlinear parts. For fault detection, two sliding mode observers (SMO) are designed for the two subsystems. The stability condition is obtained based on the Lyapunov approach. The necessary matrices and parameters are obtained by solving the linear matrix inequality (LMI) problem. Furthermore, two sliding mode observers are designed for fault isolation. Finally, the effectiveness of the proposed approach is illustrated by simulation examples.http://dx.doi.org/10.1080/00051144.2019.1706911fault detectionlipschitznonlinear systemsliding mode observerlmi |
| spellingShingle | Farideh Allahverdi Amin Ramezani Mehdi Forouzanfar Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers Automatika fault detection lipschitz nonlinear system sliding mode observer lmi |
| title | Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers |
| title_full | Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers |
| title_fullStr | Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers |
| title_full_unstemmed | Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers |
| title_short | Sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers |
| title_sort | sensor fault detection and isolation for a class of uncertain nonlinear system using sliding mode observers |
| topic | fault detection lipschitz nonlinear system sliding mode observer lmi |
| url | http://dx.doi.org/10.1080/00051144.2019.1706911 |
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