The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Neural-Based Adaptive Output-Feedback Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems
Abstract
In this paper, we consider the problem of observer-based adaptive neural output-feedback control for a class of stochastic nonlinear systems with nonstrict-feedback structure. To overcome the design difficulty from the nonstrict-feedback structure, a variable separation approach is introduced by using the monotonically increasing property of system bounding functions. On the basis of the state observer, and by combining the adaptive backstepping technique with radial basis function neural networks' universal approximation capability, an adaptive neural output feedback control algorithm is presented. It is shown that the proposed controller can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded in the sense of mean quartic value. Simulation results are provided to show the effectiveness of the proposed control scheme.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gaussian networks for direct adaptive control
Sanner, R. M., & Slotine, J.-J. E. (1992) · IEEE Transactions on Neural Networks · doi:10.1109/72.165588 · Cited by 2,195
Gaussian Networks for Direct Adaptive Control
Sanner, R. M., & Slotine, J.-J. E. (1991) · 1991 American Control Conference · doi:10.23919/acc.1991.4791778 · Cited by 1,072
Stochastic nonlinear stabilization — I: A backstepping design
Deng, H., & Krstić, M. (1997) · Systems & Control Letters · doi:10.1016/s0167-6911(97)00068-6 · Cited by 763
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Yao, B., & Tomizuka, M. (1997) · Automatica · doi:10.1016/s0005-1098(96)00222-1 · Cited by 724
Direct adaptive fuzzy control of nonlinear strict-feedback systems
Chen, B., Liu, X., Liu, K., & Lin, C. (2009) · Automatica · doi:10.1016/j.automatica.2009.02.025 · Cited by 707
Self-citationDirect 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 618
Tong, S., Li, Y., Li, Y., & Liu, Y. (2011) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2011.2159264 · Cited by 608
Decentralized adaptive output-feedback stabilization for large-scale stochastic nonlinear systems
Liu, S.-J., Zhang, J.-F., & Jiang, Z.-P. (2007) · Automatica · doi:10.1016/j.automatica.2006.08.028 · Cited by 572
A DSC Approach to Robust Adaptive NN Tracking Control for Strict-Feedback Nonlinear Systems
Li, T.-S., Wang, D., Feng, G., & Tong, S.-C. (2010) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2009.2033563 · Cited by 568
Tong, S.-C., Li, Y.-M., Feng, G., & Li, T.-S. (2011) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2011.2108283 · Cited by 498
Cited by
Li, Y., Sui, S., & Tong, S. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2016.2518300 · Cited by 417
Adaptive Fuzzy Practical Fixed-Time Tracking Control of Nonlinear Systems
Chen, M., Wang, H., & Liu, X. (2021) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2959972 · Cited by 405
Self-citationManipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks
Jin, L., Li, S., La, H. M., & Luo, X. (2017) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2017.2674624 · Cited by 382
Fuzzy Adaptive Finite-Time Control Design for Nontriangular Stochastic Nonlinear Systems
Sui, S., Chen, C. L. P., & Tong, S. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2018.2882167 · Cited by 363
Fixed-time adaptive neural tracking control for a class of uncertain nonstrict nonlinear systems
Ba, D., Li, Y.-X., & Tong, S. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.06.063 · Cited by 281
Metadata
- Authors
- Wang, H., Liu, K., Liu, X., Chen, B., & Lin, C.
- Venue
- IEEE Transactions on Cybernetics
- Published
- 2015-09
- Volume
- 45
- Issue
- 9
- Pages
- 1977-1987
- ISSN
- 2168-2267 (ISSN-L)
- 2168-2275
- OpenAlex
- W1996099152
- Cited by
- 324
- References
- 37
- FWCI
- 32.38
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Neural-Based Adaptive Output-Feedback Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems. https://app.cochat.ai/papers/10.1109/tcyb.2014.2363073
- The paper
- Wang, H., Liu, K., Liu, X., Chen, B., & Lin, C. (2015). Neural-Based Adaptive Output-Feedback Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems. IEEE Transactions on Cybernetics. https://doi.org/10.1109/tcyb.2014.2363073
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
