The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach
Abstract
In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.
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Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
Cited by
Adaptive Dynamic Programming for Control: A Survey and Recent Advances
Liu, D., Xue, S., Zhao, B., Luo, B., & Wei, Q. (2021) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2020.3042876 · Cited by 708
Self-citationTong, S., Sun, K., & Sui, S. (2018) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2017.2686373 · Cited by 551
Li, H., Wu, Y., & Chen, M. (2021) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2982168 · Cited by 422
Self-citationLiu, Y.-J., Gao, Y., Tong, S., & Li, Y. (2016) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2015.2418000 · Cited by 408
Off-Policy Reinforcement Learning for $ H_\infty $ Control Design
Luo, B., Wu, H.-N., & Huang, T. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2319577 · Cited by 362
Metadata
- Authors
- Liu, D., Wang, D., & Li, H.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2014-02
- Volume
- 25
- Issue
- 2
- Pages
- 418-428
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W1999678919
- Cited by
- 352
- References
- 2
- FWCI
- 29.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, D., Wang, D., & Li, H. (2014). Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2013.2280013
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