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Adaptive rapid neural observer-based sensors fault diagnosis and reconstruction of quadrotor unmanned aerial vehicle.

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Title: Adaptive rapid neural observer-based sensors fault diagnosis and reconstruction of quadrotor unmanned aerial vehicle.
Authors: Taimoor, Muhammad1 (AUTHOR) muhtaimoor123@hotmail.com, Lu, Xiao1 (AUTHOR) luxiao98@163.com, Maqsood, Hamid2 (AUTHOR) hamid_maqsood@yahoo.com, Sheng, Chunyang1 (AUTHOR) scy@sdust.edu.cn
Source: Aircraft Engineering & Aerospace Technology. 2021, Vol. 93 Issue 5, p847-861. 15p.
Subjects: Fault diagnosis, Drone aircraft, Radial basis functions, Algorithms, Stability theory, Dynamic positioning systems
Abstract: Purpose: The objective of this research is to investigate various neural network (NN) observer techniques for sensors fault identification and diagnosis of nonlinear system in consideration of numerous faults, failures, uncertainties and disturbances. For the importunity of increasing the faults diagnosis and reconstruction preciseness, a new technique is used for modifying the weight parameters of NNs without enhancement of computational complexities. Design/methodology/approach: Various techniques such as adaptive radial basis functions (ARBF), conventional radial basis functions, adaptive multi-layer perceptron, conventional multi-layer perceptron and extended state observer are presented. For increasing the fault detection preciseness, a new technique is used for updating the weight parameters of radial basis functions and multi-layer perceptron (MLP) without enhancement of computational complexities. Lyapunov stability theory and sliding-mode surface concepts are used for the weight-updating parameters. Based on the combination of these two concepts, the weight parameters of NNs are updated adaptively. The key purpose of utilization of adaptive weight is to enhance the detection of faults with high accuracy. Because of the online adaptation, the ARBF can detect various kinds of faults and failures such as simultaneous, incipient, intermittent and abrupt faults effectively. Results depict that the suggested algorithm (ARBF) demonstrates more confrontation to unknown disturbances, faults and system dynamics compared with other investigated techniques and techniques used in the literature. The proposed algorithms are investigated by the utilization of quadrotor unmanned aerial vehicle dynamics, which authenticate the efficiency of the suggested algorithm. Findings: The proposed Lyapunov function theory and sliding-mode surface-based strategy are studied, which shows more efficiency to unknown faults, failures, uncertainties and disturbances compared with conventional approaches as well as techniques used in the literature. Practical implications: For improvement of the system safety and for avoiding failure and damage, the rapid fault detection and isolation has a great significance; the proposed approaches in this research work guarantee the detection and reconstruction of unknown faults, which has a great significance for practical life. Originality/value: In this research, two strategies such Lyapunov function theory and sliding-mode surface concept are used in combination for tuning the weight parameters of NNs adaptively. The main purpose of these strategies is the fault diagnosis and reconstruction with high accuracy in terms of shape as well as the magnitude of unknown faults. Results depict that the proposed strategy is more effective compared with techniques used 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
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DbLabel: Engineering Source
An: 151754250
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Label: Title
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  Data: Adaptive rapid neural observer-based sensors fault diagnosis and reconstruction of quadrotor unmanned aerial vehicle.
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  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="%22Lu%2C+Xiao%22">Lu, Xiao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> luxiao98@163.com</i><br /><searchLink fieldCode="AR" term="%22Maqsood%2C+Hamid%22">Maqsood, Hamid</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> hamid_maqsood@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Sheng%2C+Chunyang%22">Sheng, Chunyang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> scy@sdust.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Aircraft+Engineering+%26+Aerospace+Technology%22">Aircraft Engineering & Aerospace Technology</searchLink>. 2021, Vol. 93 Issue 5, p847-861. 15p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+aircraft%22">Drone aircraft</searchLink><br /><searchLink fieldCode="DE" term="%22Radial+basis+functions%22">Radial basis functions</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Stability+theory%22">Stability theory</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+positioning+systems%22">Dynamic positioning systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: The objective of this research is to investigate various neural network (NN) observer techniques for sensors fault identification and diagnosis of nonlinear system in consideration of numerous faults, failures, uncertainties and disturbances. For the importunity of increasing the faults diagnosis and reconstruction preciseness, a new technique is used for modifying the weight parameters of NNs without enhancement of computational complexities. Design/methodology/approach: Various techniques such as adaptive radial basis functions (ARBF), conventional radial basis functions, adaptive multi-layer perceptron, conventional multi-layer perceptron and extended state observer are presented. For increasing the fault detection preciseness, a new technique is used for updating the weight parameters of radial basis functions and multi-layer perceptron (MLP) without enhancement of computational complexities. Lyapunov stability theory and sliding-mode surface concepts are used for the weight-updating parameters. Based on the combination of these two concepts, the weight parameters of NNs are updated adaptively. The key purpose of utilization of adaptive weight is to enhance the detection of faults with high accuracy. Because of the online adaptation, the ARBF can detect various kinds of faults and failures such as simultaneous, incipient, intermittent and abrupt faults effectively. Results depict that the suggested algorithm (ARBF) demonstrates more confrontation to unknown disturbances, faults and system dynamics compared with other investigated techniques and techniques used in the literature. The proposed algorithms are investigated by the utilization of quadrotor unmanned aerial vehicle dynamics, which authenticate the efficiency of the suggested algorithm. Findings: The proposed Lyapunov function theory and sliding-mode surface-based strategy are studied, which shows more efficiency to unknown faults, failures, uncertainties and disturbances compared with conventional approaches as well as techniques used in the literature. Practical implications: For improvement of the system safety and for avoiding failure and damage, the rapid fault detection and isolation has a great significance; the proposed approaches in this research work guarantee the detection and reconstruction of unknown faults, which has a great significance for practical life. Originality/value: In this research, two strategies such Lyapunov function theory and sliding-mode surface concept are used in combination for tuning the weight parameters of NNs adaptively. The main purpose of these strategies is the fault diagnosis and reconstruction with high accuracy in terms of shape as well as the magnitude of unknown faults. Results depict that the proposed strategy is more effective compared with techniques used 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-01-2021-0005
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 847
    Subjects:
      – SubjectFull: Fault diagnosis
        Type: general
      – SubjectFull: Drone aircraft
        Type: general
      – SubjectFull: Radial basis functions
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Stability theory
        Type: general
      – SubjectFull: Dynamic positioning systems
        Type: general
    Titles:
      – TitleFull: Adaptive rapid neural observer-based sensors fault diagnosis and reconstruction of quadrotor unmanned aerial vehicle.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Taimoor, Muhammad
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            NameFull: Lu, Xiao
      – PersonEntity:
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            NameFull: Maqsood, Hamid
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            NameFull: Sheng, Chunyang
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          Dates:
            – D: 01
              M: 06
              Text: 2021
              Type: published
              Y: 2021
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              Value: 17488842
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            – Type: volume
              Value: 93
            – Type: issue
              Value: 5
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            – TitleFull: Aircraft Engineering & Aerospace Technology
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