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Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay
Abstract
This paper addresses the problem of adaptive tracking control for a class of strict-feedback nonlinear state constrained systems with input delay. To alleviate the major challenges caused by the appearances of full state constraints and input delay, an appropriate barrier Lyapunov function and an opportune backstepping design are used to avoid the constraint violation, and the Pade approximation and an intermediate variable are employed to eliminate the effect of the input delay. Neural networks are employed to estimate unknown functions in the design procedure. It is proven that the closed-loop signals are semiglobal uniformly ultimately bounded, and the tracking error converges to a compact set of the origin, as well as the states remain within a bounded interval. The simulation studies are given to illustrate the effectiveness of the proposed control strategy in this paper.
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“Unlike studies such as [16,17], which focus solely on backlash hysteresis, or [31,32], which primarily address input delay, this paper simultaneously considers the influence of both backlash-like hysteresis and input delay in nonstrict-feedback nonlinear systems.”
From Fixed-Time Adaptive Control for Nonstrict-Feedback Nonlinear Systems with Input Delay and Unknown Backlash-Like Hysteresis (2025) · cites this paper as [31]
Citations
Cites
2 retracted
Karimi, H. R., & Gao, H. (2009) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2009.2024408 · Cited by 445
RetractedKarimi, H. R. (2011) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2011.2106090 · Cited by 327
RetractedConstrained model predictive control: Stability and optimality
Mayne, D. Q., Rawlings, J. B., Rao, C. V., & Scokaert, P. O. M. (2000) · Automatica · doi:10.1016/s0005-1098(99)00214-9 · Cited by 8,736
Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
Tee, K. P., Ge, S. S., & Tay, E. H. (2009) · Automatica · doi:10.1016/j.automatica.2008.11.017 · Cited by 2,920
Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
He, W., Chen, Y., & Yin, Z. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2411285 · Cited by 1,279
Control of nonlinear systems with time-varying output constraints
Tee, K. P., Ren, B., & Ge, S. S. (2011) · Automatica · doi:10.1016/j.automatica.2011.08.044 · Cited by 1,065
Liu, Y., & Tong, S. (2015) · Automatica · doi:10.1016/j.automatica.2015.10.034 · Cited by 885
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He, W., Dong, Y., & Sun, C. (2015) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2015.2429555 · Cited by 790
Chen, M., Ge, S. S., & How, B. V. E. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2010.2042611 · Cited by 733
Adaptive output-feedback control design with prescribed performance for switched nonlinear systems
Li, Y., Tong, S., Liu, L., & Feng, G. (2017) · Automatica · doi:10.1016/j.automatica.2017.02.005 · Cited by 669
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Shu, Y. (2023) · International Journal of Control · doi:10.1080/00207179.2023.2188432 · Cited by 10
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Sun, J., Zhang, M., Ma, L., Ding, S., & Yu, X. (2025) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2025.3597432 · Cited by 8
Sun, Y., Van, M., McIlvanna, S., Nhat, N. M., McLoone, S., Ceglarek, D. J., & Ge, S. S. (2025) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.7922 · Cited by 8
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Ren, L., Wu, J. C., & Liu, J. (2023) · International Journal of Fuzzy Systems · doi:10.1007/s40815-023-01576-0 · Cited by 8
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Wan, M., & Yin, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2987214 · Cited by 8
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Wu, P., Liu, W., & Lu, Y. (2023) · Transactions of the Institute of Measurement and Control · doi:10.1177/01423312231157794 · Cited by 7
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Sun, Y., Zhao, Q., Zhang, C., & Wu, J. M. (2020) · Circuits Systems and Signal Processing · doi:10.1007/s00034-019-01335-3 · Cited by 6
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Guo, D. M., Liu, J., Zheng, S., Cai, J., & Jiang, P. (2023) · IEEE Access · doi:10.1109/access.2023.3347807 · Cited by 5
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Wan, M., Liu, Q., Zheng, J., & Song, J. (2019) · Mathematical Problems in Engineering · doi:10.1155/2019/3683581 · Cited by 5
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Liu, S., & Li, S. (2024) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.3899 · Cited by 5
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Wan, M., & Huang, S. (2014) · Advances in Mechanical Engineering · doi:10.1177/1687814020958829 · Cited by 5
Moosapour, S. H., Ataei, M., & Ekramian, M. (2019) · IET Control Theory and Applications · doi:10.1049/iet-cta.2018.5706 · Cited by 5
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Li, C., Xu, Z., Zhao, J. Y., Ren, Q., & Song, C. (2024) · Nonlinear Dynamics · doi:10.1007/s11071-024-09876-2 · Cited by 4
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Wang, T., Xu, X., & Tang, X. (2020) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2020.1003363 · Cited by 4
Qi, X., & Liu, W. (2021) · Transactions of the Institute of Measurement and Control · doi:10.1177/01423312211058302 · Cited by 4
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Metadata
- Authors
- Li, D.-P., Liu, Y.-J., Tong, S., Chen, C. L. P., & Li, D.-J.
- Affiliations
- Liaoning University of Technology (CN)
- University of Macau (MO)
- Venue
- IEEE Transactions on Cybernetics
- Published
- 2019-04
- Volume
- 49
- Issue
- 4
- Pages
- 1249-1258
- ISSN
- 2168-2267 (ISSN-L)
- 2168-2275
- OpenAlex
- W2790630269
- Cited by
- 382
- References
- 74
- Citations by year
- 2026: 23 · 2025: 33 · 2024: 50 · 2023: 38 · 2022: 49 · 2021: 43 · 2020: 72 · 2019: 48
- FWCI
- 29.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Cybernetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (61622303, 61603164, 61773188)
- Program for Liaoning Innovative Research Team in University (LT2016006)
- Fundamental Research Funds for the Universities of Liaoning Province (JZL201715402)
- Program for Distinguished Professor of Liaoning Province
- Topics
- 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
- Physical Sciences › Engineering › Control and Systems Engineering › Neural Networks Stability and Synchronization
- Keywords
- adaptive tracking control, strict-feedback nonlinear systems, state constraints, input delay, barrier Lyapunov function, backstepping control, Padé approximants, neural network function approximation, semi-global uniform ultimate boundedness, constraint violation avoidance
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