Experimental Test of a Two-Stage Kalman Filter for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter

被引：171

作者：

Amoozgar, M. Hadi ^{[1
]}

Chamseddine, Abbas ^{[1
]}

Zhang, Youmin ^{[1
]}

机构：

[1] Concordia Univ, Dept Mech & Ind Engn, Montreal, PQ H3G 1M8, Canada

来源：

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 2013年 / 70卷 / 1-4期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Unmanned quadrotor helicopter; Actuator faults; Fault detection and diagnosis; Two-stage Kalman filter; Experimental test; SENSOR;

D O I：

10.1007/s10846-012-9757-7

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

This paper addresses the problem of Faut Detection and Diagnosis (FDD) of a quadrotor helicopter system in the presence of actuator faults. To this end a Two-Stage Kalman Filter (TSKF) is used to simultaneously estimate and isolate possible faults in each actuator. The faults are modelled as losses in control effectiveness of rotors. Three fault scenarios are investigated: loss of control effectiveness in one single actuator, simultaneous loss of control effectiveness in all motors, and loss of control effectiveness in three motors with different magnitudes. The developed FDD algorithm is evaluated through experimental application to an unmanned quadrotor helicopter testbed available at the Department of Mechanical and Industrial Engineering of Concordia University, called Qball-X4. The obtained results show the effectiveness of the proposed FDD method.

引用

页码：107 / 117

页数：11

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