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Rotorcraft UAV Actuator Failure Detection Based on a New Adaptive Set-Membership Filter

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Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 7506))

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Abstract

Actuator failure detection method based on a new Adaptive Extended Set-Membership Filter (AESMF) is proposed for Rotorcraft Unmanned Aerial Vehicle (RUAV). The AEMSF proposed in this paper is based on MIT method to optimize the set boundaries of process noises which may be incorrect in modeling or time-variant in operation; estimation stability and boundaries accuracy can be improved compared to the conventional ESMF. Actuator Healthy Coefficients (AHCs) is introduced into the dynamics of RUAV to denote the actuator failure model. Based on AESMF, online estimation of the AHCs can be obtained along with the flight state. With the estimated AHCs, actuator failure can be detected as soon as possible which provide valuable information for fault tolerant control. Efficiency and improvement of this method compared with other online parameters estimation methods is demonstrated by simulation using ServoHeli-20 model.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Robotics, Shenyang Institute and Automation, Chinese Academy of Sciences, Shenyang, 110016, China

    Chong Wu, Dalei Song, Juntong Qi & Jianda Han

  2. The Graduate School of the Chinese Academy of Sciences, Beijing, 100080, China

    Chong Wu

Authors
  1. Chong Wu

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  2. Dalei Song

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  3. Juntong Qi

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  4. Jianda Han

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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Concordia University, H3G 1M8, Montreal, Canada

    Chun-Yi Su

  2. Mechanical and Industrial Engineering, Concordia University, 1515 St. Catherine St. West, Montreal, Quebec, Canada

    Subhash Rakheja

  3. School of Creative Technologies, The University of Portsmouth, PO1 2DJ, Portsmouth, UK

    Honghai Liu

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© 2012 Springer-Verlag Berlin Heidelberg

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Wu, C., Song, D., Qi, J., Han, J. (2012). Rotorcraft UAV Actuator Failure Detection Based on a New Adaptive Set-Membership Filter. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33509-9_43

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Chapter
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JPY 5719
Price includes VAT (Japan)
  • Available as PDF
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Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
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Tax calculation will be finalised at checkout

Purchases are for personal use only


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