Neural-sliding mode approach-based adaptive estimation, isolation and tolerance of aircraft sensor fault.
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| Title: | Neural-sliding mode approach-based adaptive estimation, isolation and tolerance of aircraft sensor fault. |
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| Authors: | Taimoor, Muhammad1 (AUTHOR) muhtaimoor123@hotmail.com, Aijun, Li2 (AUTHOR) liaijun@nwpu.edu.cn |
| Source: | Aircraft Engineering & Aerospace Technology. 2020, Vol. 92 Issue 2, p237-255. 19p. |
| Subjects: | Boeing Co., Radial basis functions, Fault-tolerant computing, Fault-tolerant control systems, Discrete-time systems, Fault diagnosis, Time-varying systems, Sliding mode control |
| Abstract: | Purpose: The purpose of this paper is to propose an adaptive neural-sliding mode-based observer for the estimation and reconstruction of unknown faults and disturbances for time-varying nonlinear systems such as aircraft, to ensure preciseness in the diagnosis of fault magnitude as well as the shape without enhancement of system complexity and cost. Fault-tolerant control (FTC) strategy based on adaptive neural-sliding mode is also proposed in the existence of faults for ensuring the stability of the faulty system. Design/methodology/approach: In this paper, three strategies are presented: adaptive radial basis functions neural network (ARBFNN), conventional radial basis functions neural network (CRBFNN) and integral-chain differentiator. For the purpose of enhancement of fault diagnosis and isolation, a new sliding mode-based concept is introduced for the weight updating parameters of radial basis functions neural network (RBFNN).The main objective of updating the weight parameters adaptively is to enhance the effectiveness of fault diagnosis and isolation without increasing the computational complexities of the system. Results depict the effectiveness of the proposed ARBFNN approach in fault detection (FD) and approximation compared to CRBFNN, integral-chain differentiator and schemes existing in literature. In the second step, the FTC strategy is presented separately for each observer in the presence of unknown faults and failures for ensuring the stability of the system, which is validated on Boeing 747 100/200 aircraft. Findings: The proposed adaptive neural-sliding mode approach is investigated, which depicts more effectiveness in numerous situations such as faults, disturbances and uncertainties compared to algorithms used in literature. In this paper, both the fault approximation and isolation and the fault tolerance approaches are studied. Practical implications: For the enhancement of safety level as well as for avoiding any kind of damage, timely FD and fault tolerance have always had a significant role; therefore, the algorithms proposed in this research ensure the tolerance of faults and failures, which plays a vital role in practical life for avoiding any kind of damage. Originality/value: In this study, a new neural-sliding mode concept is adopted for the adaptive faults approximation and reconstruction, and then the FTC algorithms are studied for each observer separately, whereas in previous studies, only the fault detection and isolation (FDI) or the fault tolerance problems were studied. Results demonstrate the effectiveness of the proposed strategy compared to the approaches given in the literature. [ABSTRACT FROM AUTHOR] |
| Copyright of Aircraft Engineering & Aerospace Technology is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 141325181 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Neural-sliding mode approach-based adaptive estimation, isolation and tolerance of aircraft sensor fault. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Taimoor%2C+Muhammad%22">Taimoor, Muhammad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> muhtaimoor123@hotmail.com</i><br /><searchLink fieldCode="AR" term="%22Aijun%2C+Li%22">Aijun, Li</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> liaijun@nwpu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Aircraft+Engineering+%26+Aerospace+Technology%22">Aircraft Engineering & Aerospace Technology</searchLink>. 2020, Vol. 92 Issue 2, p237-255. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Boeing+Co%2E%22">Boeing Co.</searchLink><br /><searchLink fieldCode="DE" term="%22Radial+basis+functions%22">Radial basis functions</searchLink><br /><searchLink fieldCode="DE" term="%22Fault-tolerant+computing%22">Fault-tolerant computing</searchLink><br /><searchLink fieldCode="DE" term="%22Fault-tolerant+control+systems%22">Fault-tolerant control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Discrete-time+systems%22">Discrete-time systems</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Time-varying+systems%22">Time-varying systems</searchLink><br /><searchLink fieldCode="DE" term="%22Sliding+mode+control%22">Sliding mode control</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: The purpose of this paper is to propose an adaptive neural-sliding mode-based observer for the estimation and reconstruction of unknown faults and disturbances for time-varying nonlinear systems such as aircraft, to ensure preciseness in the diagnosis of fault magnitude as well as the shape without enhancement of system complexity and cost. Fault-tolerant control (FTC) strategy based on adaptive neural-sliding mode is also proposed in the existence of faults for ensuring the stability of the faulty system. Design/methodology/approach: In this paper, three strategies are presented: adaptive radial basis functions neural network (ARBFNN), conventional radial basis functions neural network (CRBFNN) and integral-chain differentiator. For the purpose of enhancement of fault diagnosis and isolation, a new sliding mode-based concept is introduced for the weight updating parameters of radial basis functions neural network (RBFNN).The main objective of updating the weight parameters adaptively is to enhance the effectiveness of fault diagnosis and isolation without increasing the computational complexities of the system. Results depict the effectiveness of the proposed ARBFNN approach in fault detection (FD) and approximation compared to CRBFNN, integral-chain differentiator and schemes existing in literature. In the second step, the FTC strategy is presented separately for each observer in the presence of unknown faults and failures for ensuring the stability of the system, which is validated on Boeing 747 100/200 aircraft. Findings: The proposed adaptive neural-sliding mode approach is investigated, which depicts more effectiveness in numerous situations such as faults, disturbances and uncertainties compared to algorithms used in literature. In this paper, both the fault approximation and isolation and the fault tolerance approaches are studied. Practical implications: For the enhancement of safety level as well as for avoiding any kind of damage, timely FD and fault tolerance have always had a significant role; therefore, the algorithms proposed in this research ensure the tolerance of faults and failures, which plays a vital role in practical life for avoiding any kind of damage. Originality/value: In this study, a new neural-sliding mode concept is adopted for the adaptive faults approximation and reconstruction, and then the FTC algorithms are studied for each observer separately, whereas in previous studies, only the fault detection and isolation (FDI) or the fault tolerance problems were studied. Results demonstrate the effectiveness of the proposed strategy compared to the approaches given in the literature. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Aircraft Engineering & Aerospace Technology is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1108/AEAT-05-2019-0106 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 237 Subjects: – SubjectFull: Boeing Co. Type: general – SubjectFull: Radial basis functions Type: general – SubjectFull: Fault-tolerant computing Type: general – SubjectFull: Fault-tolerant control systems Type: general – SubjectFull: Discrete-time systems Type: general – SubjectFull: Fault diagnosis Type: general – SubjectFull: Time-varying systems Type: general – SubjectFull: Sliding mode control Type: general Titles: – TitleFull: Neural-sliding mode approach-based adaptive estimation, isolation and tolerance of aircraft sensor fault. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Taimoor, Muhammad – PersonEntity: Name: NameFull: Aijun, Li IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: 2020 Type: published Y: 2020 Identifiers: – Type: issn-print Value: 17488842 Numbering: – Type: volume Value: 92 – Type: issue Value: 2 Titles: – TitleFull: Aircraft Engineering & Aerospace Technology Type: main |
| ResultId | 1 |
