Nonlinear Actuator Fault Detection for Small-Scale UASs

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• 作者：X. Yang (1)
  L. Mejias (1)
  F. Gonzalez (1)
  M. Warren (1)
  B. Upcroft (2)
  B. Arain (1)
  
• 关键词：Fault detection ; Unscented Kalman filter ; UAS ; Actuator fault
• 刊名：Journal of Intelligent and Robotic Systems
• 出版年：2014
• 出版时间：January 2014
• 年：2014
• 卷：73
• 期：1-4
• 页码：557-572
• 全文大小：6,648 KB
• 作者单位：X. Yang (1)
  L. Mejias (1)
  F. Gonzalez (1)
  M. Warren (1)
  B. Upcroft (2)
  B. Arain (1)
  
  1. Australian Research Center for Aerospace Automation (ARCAA) and Queensland University, of Technology (QUT), Brisbane, Australia
  2. School of Electrical Engineering and Computer Science, QUT, Brisbane, Australia
  
• ISSN：1573-0409

文摘

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of?UASs.