Research on Fault-Tolerant Control of High-Speed on/off Valves Based on Unknown Sensor Input Observers

As the core component of digital hydraulic systems, the precise control of high-speed <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on/off</small> valves (HSVs) largely depends on current sensor monitoring and feedback. However, sensors may fail due to aging, interference, and other factors, leading to degraded system performance. This article proposes a fault-tolerant control (FTC) method for HSV current sensors based on an unknown input sliding mode observer. First, a first-order low-pass filter is introduced to equivalently transform sensor faults into actuator faults, and coordinate transformation is employed to decouple faults and disturbances. Subsequently, an unknown input sliding mode state observer is designed to simultaneously achieve system state observation and fault disturbance reconstruction. Finally, a fault-tolerant controller is designed based on the reconstructed values. Simulation and experimental results demonstrate that the proposed method achieves precise control of HSVs in the presence of both sensor faults and external disturbances. Compared with traditional methods, the proposed approach effectively suppresses high-frequency chattering phenomena, conserves computational resources, and reduces position tracking error by 72.73% in hydraulic cylinder control applications. This research provides a new technical pathway for high-precision control of digital hydraulic systems.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industrial Electronics
Published
2025-08-19
DOI
https://doi.org/10.1109/tie.2025.3591687
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Fault-Tolerant Control of High-Speed on/off Valves Based on Unknown Sensor Input Observers

Aixiang Ma, Xihao Yan, Sihai Zhao, Dongjie Wang et al.
IEEE Transactions on Industrial Electronics
Advanced Sensor and Control Systems
article

Research on Fault-Tolerant Control of High-Speed on/off Valves Based on Unknown Sensor Input Observers

Aixiang Ma, Xihao Yan, Sihai Zhao, Dongjie Wang, Yuxin He
article en

Abstract

As the core component of digital hydraulic systems, the precise control of high-speed <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on/off</small> valves (HSVs) largely depends on current sensor monitoring and feedback. However, sensors may fail due to aging, interference, and other factors, leading to degraded system performance. This article proposes a fault-tolerant control (FTC) method for HSV current sensors based on an unknown input sliding mode observer. First, a first-order low-pass filter is introduced to equivalently transform sensor faults into actuator faults, and coordinate transformation is employed to decouple faults and disturbances. Subsequently, an unknown input sliding mode state observer is designed to simultaneously achieve system state observation and fault disturbance reconstruction. Finally, a fault-tolerant controller is designed based on the reconstructed values. Simulation and experimental results demonstrate that the proposed method achieves precise control of HSVs in the presence of both sensor faults and external disturbances. Compared with traditional methods, the proposed approach effectively suppresses high-frequency chattering phenomena, conserves computational resources, and reduces position tracking error by 72.73% in hydraulic cylinder control applications. This research provides a new technical pathway for high-precision control of digital hydraulic systems.

IEEE Transactions on Industrial ElectronicsVol. 73(1)
China University of Mining and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 75%
Advanced Sensor and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.