Cited by 148Stability and Control of Uncertain SystemsAdaptive Control of Nonlinear SystemsNeural Networks Stability and Synchronization

The DOI matches its Crossref record; 71 of the 72 references it cites were found in a registry or an index.

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints

Li, Da-Peng, Li, Dong-Juan, Liu, Yan-Jun, Tong, Shaocheng, Chen, C. L. Philip·2017·IEEE Transactions on Cybernetics

DOI 10.1109/tcyb.2017.2707178

Open this paper in CoChat — free account

Abstract

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

Integrity signals

Registry

Crossref · 10.1109/tcyb.2017.2707178

Cites

71 of 71 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

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
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function
Ren, B., Ge, S. S., Tee, K. P., & Lee, T. H. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2010.2047115 · Cited by 1,088
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
Adaptive Neural Control of Uncertain MIMO Nonlinear Systems
Ge, S. S., & Wang, C. (2004) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.826130 · Cited by 971
Barrier Lyapunov Functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints
Liu, Y., & Tong, S. (2015) · Automatica · doi:10.1016/j.automatica.2015.10.034 · Cited by 885
Self-citation
Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems
Liu, Y., & Tong, S. (2016) · Automatica · doi:10.1016/j.automatica.2016.10.011 · Cited by 831
Self-citation
Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities
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 Neural Control of Nonlinear Time-Delay Systems With Unknown Virtual Control Coefficients
Ge, S. S., Hong, F., & Lee, T. H. (2004) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2003.817055 · Cited by 717
Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning
He, W., & Dong, Y. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2665581 · Cited by 643

Flagged first, then by citations

Show all 72 references

1 of the 72 references couldn’t be matched to a known paper.

Sorted by citations

Items 101–148 of 148

Neural Network-Based Adaptive Tracking Control for a Class of Nonlinear Singularly Perturbed Systems
Wang, H., Yang, C., & Zhu, S. (2019) · IEEE Access · doi:10.1109/access.2019.2908276 · Cited by 9
Adaptive Fuzzy Fault‐Tolerant Control for CSTR With State Constraints Dependent on Temperature and Concentration
Ma, Y., Liu, L., Li, D., & Li, D. (2024) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.7782 · Cited by 8
Self-citation
Multi-variable constrained control for uncertain high-order strict-feedback fully actuated nonlinear systems
Zhu, L., Zhang, L., Qian, C., & Hua, C. (2024) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2024.107190 · Cited by 7
Tracking Control of a Continuous Stirred Tank Reactor Using Direct and Tuned Reinforcement Learning Based Controllers
Pandian, B. J., & Noel, M. M. (2017) · Chemical Product and Process Modeling · doi:10.1515/cppm-2017-0040 · Cited by 7
BLS-based adaptive fault tolerant control for a class of space unmanned systems with time-varying state constraints and input nonlinearities
Ning, X., Zhang, Y., Wang, Z. X., Yu, D., Guo, H., & Mei, H. (2021) · European Journal of Control · doi:10.1016/j.ejcon.2021.05.001 · Cited by 7
Adaptive fuzzy asymptotic control design for MIMO nonlinear systems with state constraints
Liu, Y., Zeng, B., Zhu, Q., & Wang, L. (2022) · Journal of Control and Decision · doi:10.1080/23307706.2022.2139298 · Cited by 7
Self-citation
Observer-based adaptive path tracking control for autonomous ground vehicle with singularities and time-varying delays
Zhang, S.-W., Ma, L., Li, Q., & Wang, H. (2025) · Journal of Mechanical Science and Technology · doi:10.1007/s12206-025-0236-z · Cited by 6
Time-delay systems: Recent trends and advancements
Deepak, V. D., Arun, N. K., & Shihabudheen, K. V. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.04.048 · Cited by 6
Adaptive Dynamic Surface Control Design with Asymptotic Tracking Performance for a Class of Uncertain Input-Delayed Systems
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
Gaussian mixture model based adaptive control for uncertain nonlinear systems with complex state constraints
Bai, Y., Chen, R., Zhao, Y. B., & Wang, Y. (2021) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2021.06.017 · Cited by 6
Fixed-Time Adaptive Control for Nonstrict-Feedback Nonlinear Systems with Input Delay and Unknown Backlash-Like Hysteresis
Kharrat, M., & Alhazmi, H. (2025) · Neural Processing Letters · doi:10.1007/s11063-025-11749-7 · Cited by 5
“Traditional methods based on Lyapunov-Krasovskii functionals are generally less effective in managing input delays compared to state delays [25–27].”
Backstepping control and revamped recurrent fuzzy neural network with mended ant colony optimization applied in SCRIM drive system
Lin, C. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-181201 · Cited by 5
Neural-network-based adaptive funnel control for servo mechanisms with unknown dead-zone
Wang, S., Na, J., & Ren, X. (2024) · Elsevier eBooks · doi:10.1016/b978-0-44-315574-1.00011-7 · Cited by 5
Robust Adaptive Control for Nonlinear Multi-Agent Systems: A Physics-Regularized Neural Backstepping Approach
Li, D. L., Zhang, A., Gao, Y. M., Vai, M. I., Pun, S. H., & Mu, C. (2026) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2026.3664097 · Cited by 4
Self-citation
Asymptotic Stability Control With Full-State Constraints for Nonlinear MIMO Systems and Its Application to Aircraft
Jia, F., Pan, T., Lu, J., & Li, Y. (2024) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2024.3493210 · Cited by 4
Maximum likelihood gradient identification for multivariate equation‐error moving average systems using the multi‐innovation theory
Liu, L., Ding, F., & Hayat, T. (2019) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.3007 · Cited by 4
Scalable clock synchronization analysis: A symmetric noncooperative output feedback tubes-MPC approach
Wang, T., Xu, X., & Tang, X. (2020) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2020.1003363 · Cited by 4
Neuro‐Adaptive Singularity‐Free Fixed‐Time Constrained Trajectory Tracking Control of HFVs With Specified Accuracy
Dong, Z., Lv, M., Da, X., & Zhang, Q. (2025) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.7864 · Cited by 3
Event-triggered synchronization adaptive learning control of nonlinear multi-agent systems with resilience to communication link faults
Zheng, Z., Chen, C., Xie, K., Li, Z., & Xie, S. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-09215-3 · Cited by 3
Self-citation
Novel scheme for uncertainty and disturbance estimation to control of spacecraft system with input constraint
Jamshidi, S., & Mirzaei, M. (2024) · Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · doi:10.1177/09596518241263371 · Cited by 3
New strategy to perturbation estimation and constrained control of vehicle suspension system
Sisi, Z. A., Mirzaei, M., & Rafatnia, S. (2025) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070251324262 · Cited by 3
Adaptive Iterative Learning Reliable Control of Nonrepetitive Systems With Multiple Iteration-Varying Parametric Uncertainties
Chen, Y., Huang, D., & Li, X. (2026) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2026.3661168 · Cited by 2
Command filter‐based adaptive neural event‐triggered control of MIMO pure‐feedback systems with full‐state time‐varying constraints
Zhu, X., Huang, J. H., Ding, W., & Zhang, T. (2022) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.3448 · Cited by 2
Adaptive Resilient Neural Control of Uncertain Time-Delay Nonlinear CPSs with Full-State Constraints under Deception Attacks
Chen, Z., Wang, X., Pang, N., & Shi, Y. (2023) · Entropy · doi:10.3390/e25060900 · Cited by 2
Connectivity-preserving adaptive synchronized tracking of heterogeneous spherical robots with limited communication ranges
Choi, Y. H., & Yoo, S. J. (2017) · Nonlinear Dynamics · doi:10.1007/s11071-017-3961-8 · Cited by 2
Adaptive Fuzzy Output Feedback Control for Partial State Constrained Nonlinear Pure Feedback Systems
Li-ping, W., Sun, W., & Wu, Y. (2018) · Mathematical Problems in Engineering · doi:10.1155/2018/9624938 · Cited by 2
Adaptive Finite‐Time Fault‐Tolerant Control for Half‐Vehicle Active Suspension Systems with Output Constraints and Random Actuator Failures
Lan, J., & Xu, T. (2021) · Complexity · doi:10.1155/2021/5964034 · Cited by 2
Design of Adaptive Control Scheme for Time-Varying State Constrained Incommensurate Fractional-Order Systems
Cao, B., Kang, T., & Hai, X. (2025) · Circuits Systems and Signal Processing · doi:10.1007/s00034-025-03252-0 · Cited by 1
RETRACTED: Clever backstepping control using two adaptive laws, a RRFNN and a compensated controller of SPCRIM drive system
Lin, C. (2020) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-191712 · Cited by 1
Retracted
Adaptive sliding mode control of petrochemical flare combustion process based on radial basis function network
Liu, J., Guo, N., Peng, Y.-X., Li, W., Qiao, J., Gao, X., & Xiong, W. (2024) · Chinese Journal of Chemical Engineering · doi:10.1016/j.cjche.2024.09.011 · Cited by 1
Adaptive Fault Tolerant Control of Hypersonic Flight Vehicle with State Constraints using Barrier Lyapunov Function
Peng, Z., Qi, R., & Jiang, B. (2019) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2019.8832538 · Cited by 1
Adaptive Fuzzy Consensus Tracking Control for Nonlinear Multiagent Systems with Time‐Varying Delays and Constraints
Lan, J., & Xu, T. (2021) · Complexity · doi:10.1155/2021/9940257 · Cited by 1
Command Filtered Control for Time-Delay Systems with Asymmetric Full State Constraints
Tang, L., Yang, Y., Yin, Y., & Zou, W. (2021) · China Automation Congress (CAC) · doi:10.1109/cac53003.2021.9728028 · Cited by 1
Occurrence of estrus in an ovariohysterectomized cat.
Putnam, R. W. (1966) · PubMed · Cited by 1
Adaptive point-to-point control system design using friction-based optimal state feedback
Abdelhameed, E. H. (2019) · Ain Shams Engineering Journal · doi:10.1016/j.asej.2018.07.006
Distributed differential game for nonlinear multiagent systems with unknown actuator faults and disturbance
Dai, J., Liu, C., & Sun, J. (2018) · Chinese Automation Congress · doi:10.1109/cac.2018.8623255
Extra ZD Aid to Output Tracking Control of Time-Varying Nonlinear Scalar Systems With Original Crash Solved
Zhang, Y., Shi, N., Guo, J., Yang, M., & Ling, Y. (2019) · International Conference on Information Science and Technology · doi:10.1109/icist.2019.8836787
Adaptive NN Constraint Control for Flexible Manipulator System Described by PDE Model
Xu, F., Liu, Y., & Tang, L. D. (2020) · International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS) · doi:10.1109/iccss52145.2020.9336761
Self-citation
Tumor imaging with indium-labeled biotin.
Goodwin, D. A. (1991) · PubMed
Fuzzy-based adaptive asymptotic tracking control design for uncertain MIMO nonlinear systems with state constraintsPreprint
Liu, Y., & Zhu, Q. (2021) · Research Square · doi:10.21203/rs.3.rs-480400/v1
Self-citation
Approximation-based Adaptive NN Control for Nonstrict-Feedback Nonlinear Systems with Input Delay
Ma, J., & Wang, J. (2021) · Chinese Control Conference (CCC) · doi:10.23919/ccc52363.2021.9550596
Adaptive Neural Asymptotic Tracking Control of MIMO Stochastic Non-strict-feedback Nonlinear Systems
Su, W., Niu, B., & Zhang, G. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-5912-6_12
Neural controller design for a class of nonlinear systems with time-varying delay: A bibliometric analysis-based short literature review
Wijaya, S., Gaol, F. L., Wibowo, A., & Zarlis, M. (2023) · International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) · doi:10.1109/iccosite57641.2023.10127776
Neural-adaptive controller for an isolated power converter
Kumar, R. (2024) · ISA Transactions · doi:10.1016/j.isatra.2024.11.038
Global Prescribed Performance Control of Unknown Time-Delay Feedback Linearizable Systems
Zhang, J., Liu, T., & Li, Z. (2025) · Chinese Control Conference (CCC) · doi:10.23919/ccc64809.2025.11178573
Adaptive Nussbaum Design for Asymptotic Tracking Control with Full-State Constraints
Yang, Y., Liu, G., & Li, Q. (2026) · Springer eBooks · doi:10.1007/978-981-95-4997-9_3
Multi-Variable Constrained Control for High-Order Fully Actuated Nonlinear Systems
Hua, C., Zhang, L., & Ning, P. (2026) · Springer eBooks · doi:10.1007/978-981-95-0962-1_8
Time-varying IBLFs-based adaptive fuzzy finite-time fault-tolerant control for nonlinear delayed systems with full-state constraint
Wang, X., Zhang, R., Jiao, Y., Jiao, J., Xu, Z., & Li, J. (2026) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2026.108870

Authors: Li, D.-P., Li, D.-J., Liu, Y.-J., Tong, S., & Chen, C. L. P.
Affiliations: Liaoning University of Technology (CN)
University of Macau (MO)
ORCID: Li, Dong-Juan
Liu, Yan-Jun
Tong, Shaocheng
Chen, C. L. Philip
Venue: IEEE Transactions on Cybernetics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2017-10
Volume: 47
Issue: 10
Pages: 3100-3109
ISSN: 2168-2267 (ISSN-L)
2168-2275
DOI: 10.1109/tcyb.2017.2707178
OpenAlex: W2625591652
Cited by: 148
References: 72
Citations by year: 2026: 5 · 2025: 6 · 2024: 11 · 2023: 8 · 2022: 12 · 2021: 25 · 2020: 21 · 2019: 26 · 2018: 26 · 2017: 6
FWCI: 13.57
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Transactions on Cybernetics (publishedVersion)
PubMed (publishedVersion)
Funders: National Natural Science Foundation of China (61603164, 61473139, 61622303)
Project for Distinguished Professor of Liaoning Province
Topics: Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
Physical Sciences › Engineering › Control and Systems Engineering › Neural Networks Stability and Synchronization
Keywords: tracking control, MIMO nonlinear systems, unknown time-varying delays, full-state constraints, adaptive neural network control, Lyapunov-Krasovskii functional, separation processes, barrier Lyapunov function, signal function, closed-loop boundedness
MeSH terms: Computer Simulation, Signal Processing, Computer-Assisted, Time Factors, Neural Networks, Computer, Nonlinear Dynamics

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

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks