The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index.
Neural adaptive dynamic surface control of an electro-hydraulic loading system for rail grinders
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Cited by
Phan, V. D., Truong, H. V. A., Le, V. C., Ho, S. P., & Ahn, K. K. (2025) · Scientific Reports · doi:10.1038/s41598-025-86583-x · Cited by 21
Liu, L., Shen, G., Wang, W., Guo, Q., Li, X., Zhu, Z., Guo, Y., & Wang, Q. (2024) · ISA Transactions · doi:10.1016/j.isatra.2024.09.021 · Cited by 8
Hua, C., Zhou, J., Zhang, B., Zhang, Y., & Luo, X. (2025) · Nonlinear Dynamics · doi:10.1007/s11071-024-10637-4 · Cited by 6
Dong, Z., Song, H., Liao, Y., Wang, H., Song, M., Jiang, J., & Chen, G. (2025) · Actuators · doi:10.3390/act14060261 · Cited by 6
Self-citationData-physics hybrid modeling and identification for an electro-hydraulic rail grinding system
Liu, K., Jin, T., Hu, W., & Shang, Z. (2025) · Mechatronics · doi:10.1016/j.mechatronics.2025.103393 · Cited by 1
Self-citation
Metadata
- Authors
- Liu, K.-F., Jin, T., Shang, Z.-T., & Wang, H.
- Affiliations
- Hunan University (CN)
- Corresponding author
- Jin, Tan
- Venue
- Nonlinear Dynamics
- Published
- 2024-06-10
- Volume
- 112
- Issue
- 16
- Pages
- 14191-14213
- ISSN
- 0924-090X (ISSN-L)
- 1573-269X
- OpenAlex
- W4399475429
- Cited by
- 13
- References
- 34
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 1
- FWCI
- 2.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
- Locations
- Nonlinear Dynamics (publishedVersion)
- Funders
- Natural Science Foundation of Hunan Province, China (2023JJ30147)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Physical Sciences › Engineering › Mechanical Engineering › Hydraulic and Pneumatic Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Dynamics and Control of Mechanical Systems
- Keywords
- rail grinding, dynamic surface control, radial basis function neural network, nonlinear friction compensation, disturbance observer, force tracking, rail corrugation, explosion of complexity, adaptive neural network control
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