The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Barrier Lyapunov functions-based command filtered output feedback control for full-state constrained nonlinear systems
Abstract
In this paper, an adaptive output feedback control via command filtered backstepping is proposed for a class of uncertain nonlinear systems with full-state constraints. Firstly, the “explosion of complexity” problem inherent in all the existing results of backstepping-based full-state constraints area is solved by the proposed control. Secondly, a state observer is designed to estimate the immeasurable states and the command filtered technology is utilized to cope with the problem in the present backstepping-based results of constrained nonlinear systems. Thirdly, the barrier Lyapunov functions are constructed to ensure the constraints are not transgressed. Then, an error compensating mechanism is developed to cope with filtering errors and only one adaptive law is needed for the full-state constrained nonlinear systems. An example is given to illustrate the validity and potential of the new design scheme.
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Cites
Nonlinear and adaptive control design
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Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
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Systematic design of adaptive controllers for feedback linearizable systems
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Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function
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Control of nonlinear systems with time-varying output constraints
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Finite-time command filtered backstepping control for a class of nonlinear systems
Yu, J., Shi, P., & Zhao, L. (2018) · Automatica · doi:10.1016/j.automatica.2018.03.033 · Cited by 877
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Sun, J., Yi, J., & Pu, Z. (2022) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2021.3052610 · Cited by 184
An extended state observer-based control design for electro-hydraulic position servomechanism
Shen, W., & Shen, C. (2021) · Control Engineering Practice · doi:10.1016/j.conengprac.2021.104730 · Cited by 60
Yang, G., Wang, H., Chen, J., & Zhang, H. (2020) · Nonlinear Dynamics · doi:10.1007/s11071-020-05921-y · Cited by 27
Li, F., Wang, F., Fan, L., Zhou, C., & Zong, Q. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11331-z · Cited by 2
Metadata
- Authors
- Yu, J., Zhao, L., Yu, H., & Lin, C.
- Venue
- Automatica
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 105
- Pages
- 71-79
- ISSN
- 0005-1098 (ISSN-L)
- OpenAlex
- W2925658806
- Cited by
- 285
- References
- 26
- FWCI
- 23.45
- Type
- journal article
- Language
- en
- Open access
- closed
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