A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots
Ensuring the reliability and stability of lower limb rehabilitation exoskeleton robots during rehabilitation training is of paramount importance. Sensor faults in such systems can degrade overall performance and may even pose significant safety hazards. Consequently, the effective reconstruction of...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Actuators |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-0825/14/6/277 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849472744965537792 |
|---|---|
| author | Zhe Sun Zhuguang Li Jinchuan Zheng Zhihong Man |
| author_facet | Zhe Sun Zhuguang Li Jinchuan Zheng Zhihong Man |
| author_sort | Zhe Sun |
| collection | DOAJ |
| description | Ensuring the reliability and stability of lower limb rehabilitation exoskeleton robots during rehabilitation training is of paramount importance. Sensor faults in such systems can degrade overall performance and may even pose significant safety hazards. Consequently, the effective reconstruction of sensor faults has become a critical challenge in ensuring the safe and dependable operation of lower limb rehabilitation exoskeleton robots. This paper presents a novel sensor fault reconstruction method for systems subject to unknown external disturbances. Initially, an equivalent input disturbance (EID) approach based on an improved sliding mode observer is developed to mitigate the adverse effects of disturbances on the fault reconstruction process. Subsequently, a novel high-order sliding mode observer (NHSMO) is proposed to accurately reconstruct sensor faults. In contrast to conventional sliding mode observers, the proposed NHSMO guarantees finite-time convergence of the observation error, thereby enhancing both estimation accuracy and robustness. The effectiveness of this method is validated through both simulation and experimental results, demonstrating its superior fault reconstruction capabilities and strong resilience to external disturbances. |
| format | Article |
| id | doaj-art-e900419b43b6425d8a2b9917f5b8a730 |
| institution | Kabale University |
| issn | 2076-0825 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj-art-e900419b43b6425d8a2b9917f5b8a7302025-08-20T03:24:26ZengMDPI AGActuators2076-08252025-06-0114627710.3390/act14060277A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton RobotsZhe Sun0Zhuguang Li1Jinchuan Zheng2Zhihong Man3College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaSchool of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3003, AustraliaSchool of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3003, AustraliaEnsuring the reliability and stability of lower limb rehabilitation exoskeleton robots during rehabilitation training is of paramount importance. Sensor faults in such systems can degrade overall performance and may even pose significant safety hazards. Consequently, the effective reconstruction of sensor faults has become a critical challenge in ensuring the safe and dependable operation of lower limb rehabilitation exoskeleton robots. This paper presents a novel sensor fault reconstruction method for systems subject to unknown external disturbances. Initially, an equivalent input disturbance (EID) approach based on an improved sliding mode observer is developed to mitigate the adverse effects of disturbances on the fault reconstruction process. Subsequently, a novel high-order sliding mode observer (NHSMO) is proposed to accurately reconstruct sensor faults. In contrast to conventional sliding mode observers, the proposed NHSMO guarantees finite-time convergence of the observation error, thereby enhancing both estimation accuracy and robustness. The effectiveness of this method is validated through both simulation and experimental results, demonstrating its superior fault reconstruction capabilities and strong resilience to external disturbances.https://www.mdpi.com/2076-0825/14/6/277lower limb rehabilitation exoskeleton robotsensor faultsequivalent input disturbancefault reconstructionnovel high-order sliding mode observer |
| spellingShingle | Zhe Sun Zhuguang Li Jinchuan Zheng Zhihong Man A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots Actuators lower limb rehabilitation exoskeleton robot sensor faults equivalent input disturbance fault reconstruction novel high-order sliding mode observer |
| title | A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots |
| title_full | A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots |
| title_fullStr | A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots |
| title_full_unstemmed | A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots |
| title_short | A Robust Strategy for Sensor Fault Reconstruction of Lower Limb Rehabilitation Exoskeleton Robots |
| title_sort | robust strategy for sensor fault reconstruction of lower limb rehabilitation exoskeleton robots |
| topic | lower limb rehabilitation exoskeleton robot sensor faults equivalent input disturbance fault reconstruction novel high-order sliding mode observer |
| url | https://www.mdpi.com/2076-0825/14/6/277 |
| work_keys_str_mv | AT zhesun arobuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT zhuguangli arobuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT jinchuanzheng arobuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT zhihongman arobuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT zhesun robuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT zhuguangli robuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT jinchuanzheng robuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots AT zhihongman robuststrategyforsensorfaultreconstructionoflowerlimbrehabilitationexoskeletonrobots |