The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.
Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints
Abstract
In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state constraints, an adaptive neural network control method is investigated in this paper. The state constraints are frequently emerged in the real-life plants and how to avoid the violation of state constraints is an important task. By introducing a barrier Lyapunov function (BLF) to every step in a backstepping procedure, a novel adaptive backstepping design is well developed to ensure that the full-state constraints are not violated. At the same time, one remarkable feature is that the minimal learning parameters are employed in BLF backstepping design. By making use of Lyapunov analysis, we can prove that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded and the output is well driven to follow the desired output. Finally, a simulation is given to verify the effectiveness of the method.
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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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Adaptive Fuzzy Systems and Control: Design and Stability Analysis
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Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
He, W., Chen, Y., & Yin, Z. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2411285 · Cited by 1,273
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 1,087
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 1,059
Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints
Chen, M., Ge, S. S., & Ren, B. (2011) · Automatica · doi:10.1016/j.automatica.2011.01.025 · Cited by 1,056
Liu, Y.-J., & Tong, S. (2016) · Automatica · doi:10.1016/j.automatica.2015.10.034 · Cited by 883
Self-citationAdaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation
He, W., Dong, Y., & Sun, C. (2016) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2015.2429555 · Cited by 790
Cited by
Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems
Wang, F., Chen, B., Lin, C., Zhang, J., & Meng, X. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2715980 · Cited by 473
Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay
Li, D.-P., Liu, Y.-J., Tong, S., Chen, C. L. P., & Li, D.-J. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2799683 · Cited by 382
Self-citationAdaptive 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
Self-citationAdaptive Controller Design-Based ABLF for a Class of Nonlinear Time-Varying State Constraint Systems
Liu, Y.-J., Lu, S., Li, D., & Tong, S. (2017) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2016.2633007 · Cited by 284
Self-citationAdaptive neural control for non-strict-feedback nonlinear systems with input delay
Wang, H., Liu, S., & Yang, X. (2020) · Information Sciences · doi:10.1016/j.ins.2019.09.043 · Cited by 152
Metadata
- Authors
- Liu, Y.-J., Li, J., Tong, S., & Chen, C. L. P.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2016-07
- Volume
- 27
- Issue
- 7
- Pages
- 1562-1571
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W2343036750
- Cited by
- 517
- References
- 70
- FWCI
- 63.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, Y.-J., Li, J., Tong, S., & Chen, C. L. P. (2016). Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2015.2508926
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