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Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form
Abstract
This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.
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Citations
Cited by
Tong, S., Min, X., & Li, Y. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2977175 · Cited by 512
Adaptive Fuzzy Tracking Control Design for SISO Uncertain Nonstrict Feedback Nonlinear Systems
Tong, S., Li, Y., & Sui, S. (2016) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2016.2540058 · Cited by 489
Adaptive Neural Network Control for a Class of Nonlinear Systems With Function Constraints on States
Liu, Y.-J., Zhao, W., Liu, L., Li, D., Tong, S., & Chen, C. L. P. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3107600 · Cited by 331
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
Li, Y., & Tong, S. (2017) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2016.2574913 · Cited by 264
Metadata
- Authors
- Chen, B., Zhang, H., & Lin, C.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2016-01
- Volume
- 27
- Issue
- 1
- Pages
- 89-98
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W2001218902
- Cited by
- 307
- References
- 0
- FWCI
- 23.82
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, B., Zhang, H., & Lin, C. (2016). Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2015.2412121
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