The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle
Abstract
This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.
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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
Stable adaptive neural control scheme for nonlinear systems
Polycarpou, M. M. (1996) · IEEE Transactions on Automatic Control · doi:10.1109/9.486648 · Cited by 1,547
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
The joy of feedback: nonlinear and adaptive
(1992) · IEEE Control Systems · doi:10.1109/37.165507 · Cited by 879
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 618
Chen, M., & Ge, S. S. (2013) · IEEE Transactions on Cybernetics · doi:10.1109/tsmcb.2012.2226577 · Cited by 395
Xu, B., Shi, Z., Yang, C., & Sun, F. (2014) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2311824 · Cited by 376
Self-citationLiu, Y.-J., Chen, C. L. P., Wen, G.-X., & Tong, S. (2011) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2011.2146788 · Cited by 366
Tong, S. C., Li, Y. M., & Zhang, H.-G. (2011) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2011.2146274 · Cited by 317
Finite-Approximation-Error-Based Optimal Control Approach for Discrete-Time Nonlinear Systems
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Cited by
RISE-Based Asymptotic Prescribed Performance Tracking Control of Nonlinear Servo Mechanisms
Wang, S., Na, J., & Ren, X. (2018) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2017.2769683 · Cited by 159
Ma, L., & Liu, L. (2021) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2019.2922393 · Cited by 79
Metadata
- Authors
- Xu, B., Yang, C., & Pan, Y.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2015-10
- Volume
- 26
- Issue
- 10
- Pages
- 2563-2575
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W1613039631
- Cited by
- 347
- References
- 18
- FWCI
- 50.11
- Type
- journal article
- Language
- en
- Open access
- closed
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