Experimental Investigation for RUAV's Actuator Fault Detections with AESMF
The adaptive extended set-membership filter (AESMF) algorithm for robots' online modelling is today proposed for use in this field. Compared to the traditional ESMF, this novel filter method improves estimation accuracy under variable boundaries of unknown but bounded (UBB) process noise, which...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2015-07-01
|
Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.5772/60854 |
id |
doaj-dcabea166b5d4edab339a631f4512aa9 |
---|---|
record_format |
Article |
spelling |
doaj-dcabea166b5d4edab339a631f4512aa92020-11-25T03:02:54ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142015-07-011210.5772/6085410.5772_60854Experimental Investigation for RUAV's Actuator Fault Detections with AESMFDalei Song0Juntong Qi1Liying Yang2Jianda Han3The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaThe State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaThe State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaThe State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaThe adaptive extended set-membership filter (AESMF) algorithm for robots' online modelling is today proposed for use in this field. Compared to the traditional ESMF, this novel filter method improves estimation accuracy under variable boundaries of unknown but bounded (UBB) process noise, which is often caused by the uncertainties of robotic dynamics. However, the applicability and stability of the AESMF method have not been tested in detail or demonstrated for real robotic systems. In this research, AESMF is applied for the actuator fault detections of a rotor-craft unmanned air vehicle (RUAV). The stability of AESMF is firstly analysed using mathematics and actuator healthy coefficients (AHC) are introduced for building the actuator failure model of RUAVs. AESMF is employed for the online boundary estimation of flight states and AHC parameters for fault tolerance control. Based on the proposed AESMF actuator fault estimation, flight experiments are conducted using a ServoHeli-40 RUAV platform and the flight results are compared with traditional ESMF and the adaptive extended Kalman filter (AEKF) in order to demonstrate its effectiveness, as well as for suggesting improvements for the actuator failure detection of RUAVs.https://doi.org/10.5772/60854 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dalei Song Juntong Qi Liying Yang Jianda Han |
spellingShingle |
Dalei Song Juntong Qi Liying Yang Jianda Han Experimental Investigation for RUAV's Actuator Fault Detections with AESMF International Journal of Advanced Robotic Systems |
author_facet |
Dalei Song Juntong Qi Liying Yang Jianda Han |
author_sort |
Dalei Song |
title |
Experimental Investigation for RUAV's Actuator Fault Detections with AESMF |
title_short |
Experimental Investigation for RUAV's Actuator Fault Detections with AESMF |
title_full |
Experimental Investigation for RUAV's Actuator Fault Detections with AESMF |
title_fullStr |
Experimental Investigation for RUAV's Actuator Fault Detections with AESMF |
title_full_unstemmed |
Experimental Investigation for RUAV's Actuator Fault Detections with AESMF |
title_sort |
experimental investigation for ruav's actuator fault detections with aesmf |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2015-07-01 |
description |
The adaptive extended set-membership filter (AESMF) algorithm for robots' online modelling is today proposed for use in this field. Compared to the traditional ESMF, this novel filter method improves estimation accuracy under variable boundaries of unknown but bounded (UBB) process noise, which is often caused by the uncertainties of robotic dynamics. However, the applicability and stability of the AESMF method have not been tested in detail or demonstrated for real robotic systems. In this research, AESMF is applied for the actuator fault detections of a rotor-craft unmanned air vehicle (RUAV). The stability of AESMF is firstly analysed using mathematics and actuator healthy coefficients (AHC) are introduced for building the actuator failure model of RUAVs. AESMF is employed for the online boundary estimation of flight states and AHC parameters for fault tolerance control. Based on the proposed AESMF actuator fault estimation, flight experiments are conducted using a ServoHeli-40 RUAV platform and the flight results are compared with traditional ESMF and the adaptive extended Kalman filter (AEKF) in order to demonstrate its effectiveness, as well as for suggesting improvements for the actuator failure detection of RUAVs. |
url |
https://doi.org/10.5772/60854 |
work_keys_str_mv |
AT daleisong experimentalinvestigationforruavsactuatorfaultdetectionswithaesmf AT juntongqi experimentalinvestigationforruavsactuatorfaultdetectionswithaesmf AT liyingyang experimentalinvestigationforruavsactuatorfaultdetectionswithaesmf AT jiandahan experimentalinvestigationforruavsactuatorfaultdetectionswithaesmf |
_version_ |
1724687806947655680 |