The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Command Filter-Based Adaptive Fuzzy Finite-Time Output Feedback Control of Nonlinear Electrohydraulic Servo System
Abstract
In this paper, the command filter-based adaptive fuzzy finite-time output feedback control (FOFC) is investigated for the Electro-hydraulic servo system. For the uncertainties in the system, we utilize the fuzzy logic systems (FLSs) to estimate these uncertain nonlinearities and fuzzy state observer is established to approximate the unmeasurable hydraulic cylinder stem speed and the internal cylinder force. Then, a command filter-based finite time output feedback control is proposed to achieve high tracking precision, where the tracking errors can be regulated into a small neighborhood around the equilibrium proved by the Lyapunov finite-time stability theory. Moreover, a command filter is introduced to avoid the explosion of complexity in the backstepping procedure, where a compensation mechanism is developed to compensate for filter errors. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, the control algorithms using FLS/NN are usually computationally expensive, since FLS relies heavily on the knowledge rules of expert and NN requires either online learning or offline training procedures to make the controller perform properly.”
From Compensation Function Observer-Based Backstepping Sliding-Mode Control of Uncertain Electro-Hydraulic Servo System (2024) · cites this paper as [23]
Citations
Cites
Higher-order sliding modes, differentiation and output-feedback control
Levant, A. (2003) · International Journal of Control · doi:10.1080/0020717031000099029 · Cited by 3,881
Continuous finite-time control for robotic manipulators with terminal sliding mode
Yu, S., Yu, X., Shirinzadeh, B., & Man, Z. (2005) · Automatica · doi:10.1016/j.automatica.2005.07.001 · Cited by 2,656
Merritt, H. E., & Pomper, V. (1968) · Journal of Applied Mechanics · doi:10.1115/1.3601167 · Cited by 2,632
A continuous feedback approach to global strong stabilization of nonlinear systems
Qian, C., & Lin, W. T. (2001) · IEEE Transactions on Automatic Control · doi:10.1109/9.935058 · Cited by 1,383
Yao, J., Jiao, Z., & Ma, D. (2014) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2304912 · Cited by 707
Chen, M., & Ge, S. S. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2015.2455053 · Cited by 501
Self-citationActive Disturbance Rejection Adaptive Control of Hydraulic Servo Systems
Yao, J., & Deng, W. (2017) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2694382 · Cited by 422
Fuzzy Adaptive Finite-Time Control Design for Nontriangular Stochastic Nonlinear Systems
Sui, S., Chen, C. L. P., & Tong, S. (2018) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2018.2882167 · Cited by 366
Adaptive Control of Hydraulic Actuators With LuGre Model-Based Friction Compensation
Yao, J., Deng, W., & Jiao, Z. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2015.2423660 · Cited by 343
Adaptive Backstepping Control of an Electrohydraulic Actuator
Ahn, K. K., Nam, D. N. C., & Jin, M. (2013) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2013.2265312 · Cited by 324
Research works printed but not linked: 1
- wu, 2018, Anti-saturation dynamic surface control for spacecraft terminal safe approach based on command filter, Int J Innov Comput Inf Control, 14, 33
Cited by
Sorted by citations
Items 201–300 of 659
Zhu, J., Ma, J., Wu, J., & Fan, L. (2025) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2025.113006 · Cited by 15
Jiang, R., Fang, F., Rodriguez-Andina, J. J., Song, Z., Liu, J., Chen, Y., & Wang, H. (2025) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2025.116321 · Cited by 22
Shi, H., Xie, Y., Wang, C., Liu, Y., Zhang, H., Li, W., Zhang, S., He, R., Sun, Y., Li, G., et al. (2022) · Tribology International · doi:10.1016/j.triboint.2022.107948 · Cited by 16
High-order Synchrosqueezing Superlets Transform and its application to mechanical fault diagnosis
Yi, C., Liu, J., Yu, Z., Huang, T., Zhou, T., Guo, G., & Liu, J. (2023) · Applied Acoustics · doi:10.1016/j.apacoust.2023.109226 · Cited by 15
Health monitoring of triboelectric self-sensing bearings through deep learning
Han, T., Ding, X., Hu, H., Peng, Z., Shi, X., & Hu, S. (2023) · Measurement · doi:10.1016/j.measurement.2023.113330 · Cited by 15
Li, Y., & Yan, P. (2023) · Energy Reports · doi:10.1016/j.egyr.2023.07.044 · Cited by 15
Mun, J., Kim, J., Do, Y., Kim, H., Lee, C., & Jeong, J. (2023) · Processes · doi:10.3390/pr11092751 · Cited by 15
Dong, L., & Wang, J. (2023) · Optics and Lasers in Engineering · doi:10.1016/j.optlaseng.2023.107821 · Cited by 15
Cybersecurity in neural interfaces: Survey and future trends
Jiang, X., Fan, J., Zhu, Z., Wang, Z., Guo, Y., Liu, X., Jia, F., & Dai, C. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107604 · Cited by 19
A Review of Fuzzy Logic Method Development in Hydraulic and Pneumatic Systems
Filo, G. (2023) · Energies · doi:10.3390/en16227584 · Cited by 15
Zhang, H., Han, W., Bai, C., Li, W., Wang, X. H., & Liu, Y. (2024) · Physica Scripta · doi:10.1088/1402-4896/ad9c29 · Cited by 15
Yue, Y., Wang, H., Zhang, P. L., & Gu, F. (2024) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2024.112209 · Cited by 15
Fang, L., Hou, M., Huang, B., Chen, G., & Yang, J. (2024) · Information Sciences · doi:10.1016/j.ins.2024.121772 · Cited by 15
Zhang, B., Wan, S., Zhao, X., Wang, C., Zhang, X., & Sheng, X. (2025) · Measurement · doi:10.1016/j.measurement.2025.117565 · Cited by 15
Contrastive learning in brain imaging
Xu, X., & Wong, S. T. C. (2025) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2025.102500 · Cited by 15
Fang, X., Wang, H., Liu, G., & Xie, Y. (2025) · Structural Health Monitoring · doi:10.1177/14759217251371673 · Cited by 14
Lian, Z., Zhou, Z., Zhang, X., Feng, Z., Han, X., & Hu, C. (2023) · Entropy · doi:10.3390/e25030442 · Cited by 14
Li, Z., Meng, Z., Liu, J., Soutis, C., & Gibson, A. A. P. (2023) · Measurement Science and Technology · doi:10.1088/1361-6501/acf9c1 · Cited by 14
An adaptive model for time-varying speed fault diagnosis under strong noise interference
Wang, H., Xue, G., & Du, W. (2024) · Journal of Mechanical Science and Technology · doi:10.1007/s12206-024-0503-4 · Cited by 15
Liu, J., Zhuang, Y., Mu, C., Liu, J., & Sun, C. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3545190 · Cited by 14
Deep learning-based classification of dementia using image representation of subcortical signals
Ranjan, S., Tripathi, A., Shende, H., Badal, R., Kumar, A., Yadav, P., Joshi, D., & Kumar, L. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-02924-w · Cited by 14
Liu, M., Gong, Y., Sun, J., Tang, B., Sun, Y., Zu, X., & Zhao, J. (2023) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2023.110410 · Cited by 13
Shao, Q., Fan, S., & Liu, F. (2023) · Nondestructive Testing And Evaluation · doi:10.1080/10589759.2023.2249583 · Cited by 13
Xu, Z., Liu, C., Wei, K., Gong, D., Heng, X., Huang, X., Gong, D., Wang, F., Wang, W., Zhai, Y., et al. (2024) · Optics & Laser Technology · doi:10.1016/j.optlastec.2024.110554 · Cited by 13
Chae, M., Kim, H., Oh, H. J., Park, C. H., Suh, C., Yoon, H., & Youn, B. D. (2024) · Journal of Computational Design and Engineering · doi:10.1093/jcde/qwae052 · Cited by 13
Enhanced early diagnosis of Alzheimer’s disease with HybridCA-Net: A multimodal fusion approach
Zhou, W., Luo, W., Gong, L., & Peng, B. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128580 · Cited by 13
Li, C., Wang, Y., Zhang, G., Qin, Y., & Tang, B. (2023) · Measurement Science and Technology · doi:10.1088/1361-6501/accbdc · Cited by 13
Chen, Y., Zhang, Y., Li, H., Yu, Z., & Liu, Y. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103960 · Cited by 12
Chen, Y., & Liu, C. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.111980 · Cited by 12
Li, X., Lv, S., Tong, C., Qin, Y., Chen, L., Ma, Y., Li, M., Luo, H., & Yin, S. (2023) · Medical Physics · doi:10.1002/mp.16302 · Cited by 12
Li, S., Xing, B., Fang, X., Wang, K., Gao, Y., Wei, Q., & Han, B. (2023) · Results in Physics · doi:10.1016/j.rinp.2023.106546 · Cited by 12
Ren, W., Zheng, Z., Zhang, C., Liu, J., & Liu, X. (2023) · Measurement · doi:10.1016/j.measurement.2023.113501 · Cited by 12
Decentralized federated domain generalization with cluster alignment for fault diagnosis
Xu, D., Jia, M., Chen, T., Liu, Y., Chai, T., & Yang, T. (2024) · Control Engineering Practice · doi:10.1016/j.conengprac.2024.105951 · Cited by 13
A novel error modulation rotation scheme for dual-axis rotational inertial navigation system
Wei, D., Guan, B., Fu, Q., & Li, S. (2024) · Measurement Science and Technology · doi:10.1088/1361-6501/ad50f5 · Cited by 12
Wang, X., Wang, B., & Yu, J. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3406830 · Cited by 12
Cao, Y., Fan, S., Tang, Y., Shan, Q., Gao, C., Sepúlveda, N., Hou, D., & Zhang, G. (2024) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2024.102117 · Cited by 12
A multi-scale dual-decoder autoencoder model for domain-shift machine sound anomaly detection
Chen, S., Sun, Y., Wang, J., Wan, M., Liu, M., & Li, X. (2024) · Digital Signal Processing · doi:10.1016/j.dsp.2024.104813 · Cited by 12
Singh, A. N., Shrivastava, R., & Srivastava, A. (2024) · Expert Systems · doi:10.1111/exsy.13770 · Cited by 12
Guo, B., Huo, H., Liu, X., Zheng, B., & Li, J. (2025) · Signal Processing · doi:10.1016/j.sigpro.2025.109889 · Cited by 12
Self-citationHong, M., Sima, C., Sun, Y., Xu, J., Li, K., Zhang, L., Wang, L., Ming, Z., & Lu, P. (2025) · Optics Express · doi:10.1364/oe.550180 · Cited by 12
Xie, S., Li, H., Zang, Y., Cao, J., Zhou, D., Tan, M., Ding, Z., & Wang, G. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113262 · Cited by 12
Deepfake detection with domain generalization and mask-guided supervision
Li, J., Hu, Y., Liu, B., She, H., & Li, C. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111622 · Cited by 14
Self-citationHuang, M., Yang, L., Jiang, G., Hao, X., Lu, H., Luo, H., Wang, P., & Li, J. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.105513 · Cited by 15
Self-citationLuo, Q., Wang, J., Gao, M., He, Z., Yang, Y., & Zhou, H. (2022) · Electronics · doi:10.3390/electronics11162586 · Cited by 12
A new method for disease diagnosis based on hierarchical BRB with power set
Han, W., Kang, X., He, W., Li, J., Li, H., & Xu, B. H. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e13619 · Cited by 12
Self-citationLightweight Target Detection for Coal and Gangue Based on Improved Yolov5s
Cao, Z., Fang, L., Li, Z., & Li, J. (2023) · Processes · doi:10.3390/pr11041268 · Cited by 12
Self-citationRapid detection of dissolved acetylene in oil based on T‐type photoacoustic cell
Wang, G., Dehui, F., Yuan, S., Li, C., Han, X., Du, J., Du, F., & Chen, K. (2023) · Microwave and Optical Technology Letters · doi:10.1002/mop.33793 · Cited by 12
Research on Robot Grasping Based on Deep Learning for Real-Life Scenarios
Hu, J., Li, Q., & Bai, Q. (2023) · Micromachines · doi:10.3390/mi14071392 · Cited by 12
Miao, D., Feng, K., Xiao, Y., Li, Z., & Gao, J. (2024) · Sensors · doi:10.3390/s24030941 · Cited by 11
Xu, D., Xiao, X., & Zhang, J. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108220 · Cited by 12
Zhu, Y., Wu, Q., Chen, B., Zhang, Q., & Wu, H. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3460880 · Cited by 11
Sheng, H., Cao, L. N. Y., Shang, Y., Li, C., Zhou, Z., Jiang, Y., Sun, Y., Tang, W., Chen, B., Guo, W., et al. (2025) · Nano Energy · doi:10.1016/j.nanoen.2025.110694 · Cited by 11
Patel, A. N., & Srinivasan, K. (2025) · Physica Medica · doi:10.1016/j.ejmp.2025.104914 · Cited by 12
SafetyGPT: An autonomous agent of electrical safety risks for monitoring workers’ unsafe behaviors
Li, W., Ma, F., Zuo, Z., Jia, R., Wang, B. Y., & Alharbi, A. M. (2025) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2025.110672 · Cited by 15
ISCDFuse: Interval sampling correlation driven visual state space models for multimodal image fusion
Zhang, L., Wang, L., Wu, Y., Chen, M., Zheng, D., & Cai, Y. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130329 · Cited by 11
BAI, Y., YAO, J., HU, J., & FENG, G. (2025) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2024.07.041 · Cited by 11
Online assessment of multi-parameter stability region and stability margin of wind power plants
Wang, P., Ma, Y., & Zhao, H. (2023) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2023.109413 · Cited by 10
Metal film thickness measurement using phase linearity feature for immunity to lift-off effect
Chen, W., & Wu, D. (2023) · NDT & E International · doi:10.1016/j.ndteint.2023.102965 · Cited by 10
A star identification algorithm for rolling shutter exposure based on Hough transform
Wang, T., Wang, G., Wei, X., & Li, Y. (2023) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2023.12.032 · Cited by 10
Sun, X., Lai, J., Lyu, P., Liu, R., & Gao, W. (2024) · Sensors · doi:10.3390/s24020597 · Cited by 10
Qin, B., Fan, W., Wang, Z., Wang, R., Xia, H., Li, F., Liu, Z., & Quan, W. (2024) · Measurement · doi:10.1016/j.measurement.2024.115487 · Cited by 10
Lu, X., Jiang, Y., Hong, H., Sun, Q. L., & Zhuo, C. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681478 · Cited by 10
Zhang, J., Wang, X., Su, Z., Lian, P., Xu, H., Zou, J., & Fan, S. (2024) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2024.110708 · Cited by 10
Jin, T., Yang, X., Qi, C., Wu, Y., Zhang, Y., & Xu, W. (2025) · Ocean Engineering · doi:10.1016/j.oceaneng.2025.121218 · Cited by 10
Liu, J., Liu, Z., Liu, Z., & Zhao, K. (2025) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2025.112771 · Cited by 10
A multi-level detection guided and co-encoding network for infrared and visible image fusion
Zheng, B., Wang, R.-H., Liu, X., & Li, J. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111778 · Cited by 10
Self-citationContinual multi-target domain adaptation for industrial process fault diagnosis
Li, S., Chen, X., Zhang, H., & Yu, J. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.111239 · Cited by 10
Wang, Y., Liu, S., Lv, S., & Liu, G. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.113616 · Cited by 11
Shang, Z., Pang, T., Pan, C., Yao, L., & Wang, Z. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111852 · Cited by 10
In Situ Calibration of Coils Constant in a Spin-Exchange Relaxation-Free (SERF) Co-magnetometer
Cao, Q., Liu, Y., Tang, J., Zhao, T., Heng, X., & Zhai, Y. (2023) · Measurement · doi:10.1016/j.measurement.2023.112812 · Cited by 10
Li, S., Ma, G., Gao, H., Xu, H., & Shao, K. (2023) · Aerospace Science and Technology · doi:10.1016/j.ast.2023.108310 · Cited by 10
Cai, Y., Zhang, J., Jiang, T., Wang, J., & Zhao, Y. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3276015 · Cited by 10
Efficient and Lightweight Neural Network for Hard Hat Detection
He, C., Tan, S., Zhao, J. C., Ergu, D., Liu, F., Ma, B., & Li, J. (2024) · Electronics · doi:10.3390/electronics13132507 · Cited by 10
Self-citationAdaptive Optimal Tracking Control of Servo Mechanisms via Generalized Policy Learning
Zhao, J., Lv, Y., Zhao, Z., & Wang, Z. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3457963 · Cited by 10
Li, Z., Meng, Z., Fei, F., & Chen, Z. (2022) · NDT & E International · doi:10.1016/j.ndteint.2022.102680 · Cited by 10
Liu, C., McCann, H. A., & Xu, L. (2023) · Measurement Science and Technology · doi:10.1088/1361-6501/ace72f · Cited by 10
Pan, C., Wang, Y., Yang, S. X., Li, Z., & Xiao, J. (2024) · Machines · doi:10.3390/machines12100719 · Cited by 16
Kurniawan, E., Wang, H., Prakosa, J. A., Purwowibowo, P., & Pratiwi, E. B. (2023) · ISA Transactions · doi:10.1016/j.isatra.2023.12.035 · Cited by 9
Chen, J., Du, X., Fei, Z., Xia, W., & Sun, X. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3368468 · Cited by 9
Machine Vision for Solid Waste Detection
Pimenov, A., Nesteruk, S., Mazanov, G., Ilyushina, A. N., Stepanov, A., Mikhailova, N., & Somov, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-59531-8_12 · Cited by 9
COD: Learning Conditional Invariant Representation for Domain Adaptation Regression
Yang, H.-R., Ren, C.-X., & Luo, Y.-W. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73116-7_7 · Cited by 9
Time-varying speed fault diagnosis based on dual-channel parallel multi-scale information
Wang, H., Xue, G., Li, Y., Li, S., Guo, Z., & Du, W. (2024) · Journal of Mechanical Science and Technology · doi:10.1007/s12206-024-1016-x · Cited by 8
DSAFuse: Infrared and visible image fusion via dual-branch spatial adaptive feature extraction
Shen, S., Feng, Y., Liu, N., Liu, M., & Li, Y. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128957 · Cited by 9
Dual-attention enhanced variational encoding for interpretable remaining useful life prediction
Liu, W., Chiang, J., Liu, G., & Zhang, H. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.129487 · Cited by 9
Li, H., Wu, S., Deng, L., Liu, C., Chen, Y., Chen, H., Yu, H., Dong, M., & Zhu, L. (2025) · The Visual Computer · doi:10.1007/s00371-025-03840-w · Cited by 10
Adaptive shape imitation and selective semantic guidance for industrial surface defect detection
Liang, X., Li, Y. Y., Wang, X., Liu, P., Shen, Y., & Guo, J. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.127334 · Cited by 12
Self-citationYuan, Y., Wei, Y., Guo, Y., Chen, J., & Jiang, T. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9040092 · Cited by 9
Finite-time event-triggered prescribed control for stochastic systems with dead-zone
Li, J., Yan, H., Ji, R., Liang, X., & Ge, S. S. (2025) · Fuzzy Sets and Systems · doi:10.1016/j.fss.2025.109406 · Cited by 11
Self-citationA dynamic weighted feature fusion lightweight algorithm for safety helmet detection based on YOLOv8
Ren, H., Fan, A., Zhao, J., Song, H., Wen, Z., & Lü, S. (2025) · Measurement · doi:10.1016/j.measurement.2025.117572 · Cited by 14
Miao, Y., Xia, Y., & Chang, J. (2025) · Measurement Science and Technology · doi:10.1088/1361-6501/adfcfb · Cited by 9
DD-YOLO: A dual-channel dual-path YOLO network for target detection of blurred vehicles
Duan, C., Guo, Y., Duan, X., Li, G., & Sheng, B. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105565 · Cited by 9
Sun, Y., Dong, M., & Zhu, L. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112788 · Cited by 10
Deng, F., Hao, R., Yang, S., Luo, B., & Jin, S. (2026) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2026.112193 · Cited by 9
A Denoising Method Using Deep Image Prior to Human-Target Detection Using MIMO FMCW Radar
Endo, K., Yamamoto, K., & Ohtsuki, T. O. (2022) · Sensors · doi:10.3390/s22239401 · Cited by 9
Павлович, Д. В., Ostertak, D. I., Pelmenev, K. G., Sinitskiy, R. E., & Dragunova, E. V. (2023) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2023.114162 · Cited by 9
Design of double-cross-based smartphone unlock mechanism
Li, W., Tan, J., & Zhu, N. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103204 · Cited by 9
Luo, Z., Qi, R., Li, Q., Zheng, J. J., & Shao, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28124-2_15 · Cited by 9
Khan, M. A., Mehmood, A., Kadry, S., Almujally, N. A., Alhaisoni, M. M., Balili, J., Hejaili, A. A., Alanazi, A., Alsubai, S., & Alqatani, A. (2023) · Future Generation Computer Systems · doi:10.1016/j.future.2023.05.011 · Cited by 9
Wang, X., Gao, Y., & Wei, Z. (2023) · Optics Express · doi:10.1364/oe.492498 · Cited by 9
DSA-Net: Infrared and Visible Image Fusion via Dual-Stream Asymmetric Network
Yin, R., Yang, B. F., Huang, Z., & Zhang, X. (2023) · Sensors · doi:10.3390/s23167097 · Cited by 9
Metadata
- Authors
- Li, J., Ji, R., Liang, X., Ge, S. S., & Yan, H.
- Affiliations
- Beijing Jiaotong University (CN)
- National University of Singapore (SG)
- Venue
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2022
- Volume
- 71
- Pages
- 1-10
- ISSN
- 0018-9456 (ISSN-L)
- 1557-9662
- OpenAlex
- W4313124175
- Cited by
- 659
- References
- 57
- Citations by year
- 2026: 11 · 2025: 250 · 2024: 225 · 2023: 143 · 2022: 30
- FWCI
- 61.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Instrumentation and Measurement (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Hydraulic and Pneumatic Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Keywords
- electro-hydraulic servo system, command filter, adaptive fuzzy control, fuzzy observer, backstepping control, tracking precision
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review