The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index.
Adaptive Intelligent Control of Nonaffine Nonlinear Time-Delay Systems With Dynamic Uncertainties
Abstract
Adaptive neural intelligent control is investigated for a class of pure-feedback nonlinear time-delay systems with unmodeled dynamics in nonlower-triangular form, which views the lower-triangular structure as a special structure. A variable partition technique is applied to surmount the difficulty in the nonlinear functions of whole state variables. By utilizing the backstepping recursive design approach and the universal approximation capability of neural networks, an adaptive neural controller is systemically designed. Then, based on the utilization of Lyapunov-Krasovskii functionals, the semiglobally uniform boundedness of all closed-loop signals is guaranteed. Finally, the suggested control method is verified through a numerical example. The main advantage of this paper is that an intelligent control method is developed for pure-feedback nonlinear systems with state time delay, unmodeled dynamics and nonlower triangular form. Further developments will focus on how to deal with the problem of output feedback control of pure-feedback nonlinear time-delay systems with unmodeled dynamics and nonlower-triangular structure.
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“Traditional methods based on Lyapunov-Krasovskii functionals are generally less effective in managing input delays compared to state delays [25][26][27].”
From Fixed-Time Adaptive Control for Nonstrict-Feedback Nonlinear Systems with Input Delay and Unknown Backlash-Like Hysteresis (2025) · cites this paper as [26]
Citations
Cites
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Liu, Y., & Tong, S. (2016) · Automatica · doi:10.1016/j.automatica.2016.10.011 · Cited by 831
Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form
Zhang, T. P., & Ge, S. S. (2008) · Automatica · doi:10.1016/j.automatica.2007.11.025 · Cited by 754
Design of Robust Adaptive Controllers for Nonlinear Systems with Dynamic Uncertainties
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Chen, C. L. P., Wen, G., Liu, Y., & Wang, F. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2014.2302477 · Cited by 634
Direct adaptive NN control of a class of nonlinear systems
Ge, S. S., & Wang, C. (2002) · IEEE Transactions on Neural Networks · doi:10.1109/72.977306 · Cited by 621
Tong, S., Zhang, L., & Li, Y. (2015) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2015.2426131 · Cited by 541
Liu, Y., Li, J., Tong, S., & Chen, C. L. P. (2016) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2508926 · Cited by 517
Cited by
Sorted by citations
LSTM Fully Convolutional Networks for Time Series Classification
Karim, F., Majumdar, S., Darabi, H., & Chen, S. (2017) · IEEE Access · doi:10.1109/access.2017.2779939 · Cited by 1,560
“especially in control systems [13], [14].”
Adaptive Finite-Time Tracking Control of Nonlinear Systems With Dynamics Uncertainties
Wang, H., Xu, K., & Zhang, H. (2023) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2022.3226703 · Cited by 342
Self-citationNonsingular Fixed-Time Fault-Tolerant Fuzzy Control for Switched Uncertain Nonlinear Systems
Cui, D., & Xiang, Z. (2022) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2022.3184048 · Cited by 193
“Among these results, fuzzy logic systems (FLSs) [12] and neural networks (NNs) [13] with powerful estimation ability are utilized frequently to estimate unknown nonlinear dynamics [14]–[20].”
BackgroundAdaptive Neural Control of Nonlinear Systems With Unknown Control Directions and Input Dead-Zone
Wang, H., Karimi, H. R., Liu, P. X., & Yang, H. (2017) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2017.2709813 · Cited by 184
Self-citationZhao, B., Wang, D., Shi, G., Liu, D., & Li, Y. (2017) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2017.2690665 · Cited by 177
“[6], [7] proposed adaptive neural control schemes for nonlinear systems with dynamic uncertainties and completely unknown dynamics.”
Background
Metadata
- Authors
- Wang, H., Sun, W., & Liu, P. X.
- Affiliations
- Carleton University (CA)
- Bohai University (CN)
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Published
- 2017-07
- Volume
- 47
- Issue
- 7
- Pages
- 1474-1485
- ISSN
- 2168-2216 (ISSN-L)
- 2168-2232
- OpenAlex
- W2558651951
- Cited by
- 151
- References
- 63
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 4 · 2023: 7 · 2022: 14 · 2021: 7 · 2020: 13 · 2019: 20 · 2018: 33 · 2017: 38
- FWCI
- 25.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Systems Man and Cybernetics Systems (publishedVersion)
- Funders
- National Natural Science Foundation of China (61304002, 61175072, 61473160)
- Natural Science Foundation of Liaoning Province of China (2015020058)
- 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 neural network control, pure-feedback nonlinear systems, time-delay systems, unmodeled dynamics, backstepping control, Lyapunov-Krasovskii functional, state delay
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