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Robust Adaptive Neural Tracking Control for a Class of Stochastic Nonlinear Interconnected Systems
Abstract
In this paper, an adaptive neural decentralized control approach is proposed for a class of multiple input and multiple output uncertain stochastic nonlinear strong interconnected systems. Radial basis function neural networks are used to approximate the packaged unknown nonlinearities, and backstepping technique is utilized to construct an adaptive neural decentralized controller. The proposed control scheme can guarantee that all signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded in the sense of fourth moment, and the tracking errors eventually converge to a small neighborhood around the origin. The main feature of this paper is that the proposed approach is capable of controlling the stochastic systems with strong interconnected nonlinearities both in the drift and diffusion terms that are the functions of all states of the overall system. Simulation results are used to illustrate the effectiveness of the suggested approach.
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Cited by
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
Adaptive Neural Control of Stochastic Nonlinear Time-Delay Systems With Multiple Constraints
Wang, T., Qiu, J., & Gao, H. (2017) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2016.2562511 · Cited by 170
Li, D.-P., Li, D.-J., Liu, Y.-J., Tong, S., & Chen, C. L. P. (2017) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2707178 · Cited by 148
Metadata
- Authors
- Wang, H., Liu, X., & Liu, K.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2016-03
- Volume
- 27
- Issue
- 3
- Pages
- 510-523
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W1998869641
- Cited by
- 229
- References
- 0
- FWCI
- 34.33
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, H., Liu, X., & Liu, K. (2016). Robust Adaptive Neural Tracking Control for a Class of Stochastic Nonlinear Interconnected Systems. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2015.2412035
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