The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
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.
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
“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
Self-citationAdaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation
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
Self-citation
Cited by
Sorted by citations
Zhao, K., & Song, Y. (2018) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2018.2845707 · Cited by 569
Liu, L., Liu, Y., & Tong, S. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2828308 · Cited by 481
Self-citationAdaptive Neural Network Control for a Class of Nonlinear Systems With Function Constraints on States
Liu, Y., Zhao, W., Liu, L., Li, D., Tong, S., & Chen, C. L. P. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3107600 · Cited by 334
Self-citationLiu, Y., Zeng, Q. H., Tong, S., Chen, C. L. P., & Liu, L. (2019) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2019.2893847 · Cited by 291
Self-citationControl of nonlinear systems under dynamic constraints: A unified barrier function-based approach
Zhao, K., Song, Y., Chen, C. L. P., & Chen, L. (2020) · Automatica · doi:10.1016/j.automatica.2020.109102 · Cited by 273
Self-citation
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
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
