A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 13
Issue 9
IEEE/CAA Journal of Automatica Sinica
| Citation: | C. Zhang, F. Xiao, X. Zhang, B. Wei, and P. Liu, “Optimal control of nonlinear systems via predefined-time convergent reinforcement learning,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 9, pp. 2178–2180, Sep. 2026. doi: 10.1109/JAS.2025.125699
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| [1] |
Z. Zhang, W. Yan, and H. Li, “Distributed optimal control for linear multiagent systems on general digraphs,” Trans. Autom. Control, vol. 66, no. 1, pp. 322−328, Jan. 2021. doi: 10.1109/TAC.2020.2974424
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| [2] |
Y. Yu, G. Liu, Y. Huang, and P. Shi, “Optimal cooperative secondary control for islanded DC microgrids via a fully actuated approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 2, pp. 405−417, Feb. 2024. doi: 10.1109/JAS.2023.123942
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| [3] |
Y. Zheng, A. Lai, X. Yu, and W. Lan, “Early-awareness collision avoidance in optimal multi-agent path planning with temporal logic specifications,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp. 1346−1348, May 2023. doi: 10.1109/JAS.2022.106043
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| [4] |
X. Liu, G. Li, L. Zhou, C. Yang, and X. Chen, “Reinforcement learning reduced H∞ output tracking control of nonlinear two-time-scale industrial systems,” IEEE Trans. Ind. Inform., vol. 20, no. 2, pp. 2465−2476, Feb. 2024. doi: 10.1109/TII.2023.3292970
|
| [5] |
D. Zhao, Z. Xia, and D. Wang, “Model-free optimal control for affine nonlinear systems with convergence analysis,” IEEE Trans. Autom. Sci. Eng., vol. 12, no. 4, pp. 1461−1468, Oct. 2015. doi: 10.1109/TASE.2014.2348991
|
| [6] |
K. Zhang, B. Zhou, M. Hou, and G.-R. Duan, “Practical prescribed-time stabilization of a class of nonlinear systems by event-triggered and self-triggered control,” IEEE Trans. Autom. Control, vol. 69, no. 5, pp. 3426−3433, May 2024. doi: 10.1109/TAC.2023.3338749
|
| [7] |
N.-M. T. Kokolakis and K. G. Vamvoudakis, “Safety-aware pursuit-evasion games in unknown environments using Gaussian processes and finite-time convergent reinforcement learning,” IEEE Trans. Neural Netw. Learn. Syst., vol. 35, no. 3, pp. 3130−3143, Mar. 2024. doi: 10.1109/TNNLS.2022.3203977
|
| [8] |
Z. Gong, F. Yang, Y. Yuan, Q. Ma, and W. X. Zheng, “Secure formation control of multi-agent system against FDI attack using fixed-time convergent reinforcement learning,” IEEE Trans. Control Netw. Syst., vol. 12, no. 2, pp. 1203−1214, Jun. 2025.
|
| [9] |
N.-M. T. Kokolakis, K. G. Vamvoudakis, and W. M. Haddad, “Fixed-time learning for optimal feedback control,” in Proc. Int. Des. Eng. Tech. Conf. Comput. Inf. Eng. Conf., Boston, USA, 2023, Art. no. DETC2023-117007.
|
| [10] |
Y. Fu and T. Chai, “Online solution of two-player zero-sum games for continuous-time nonlinear systems with completely unknown dynamics,” IEEE Trans. Neural Netw. Learn. Syst., vol. 27, no. 12, pp. 2577−2587, Dec. 2016. doi: 10.1109/TNNLS.2015.2496299
|
| [11] |
V. K. Singh, S. Kamal, B. Bandyopadhyay, S. Ghosh, and T. N. Dinh, “Prescribed-time optimal control of nonlinear dynamical systems with application to a coupled tank system,” IEEE Trans. Autom. Sci. Eng., vol. 22, pp. 191−201, Jan. 2025. doi: 10.1109/TASE.2023.3349068
|
| [12] |
K. Hornik, M. Stinchcombe, and H. White, “Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks,” Neural Netw., vol. 3, no. 5, pp. 551−560, Jan. 1990. doi: 10.1016/0893-6080(90)90005-6
|
| [13] |
H. Modares, F. L. Lewis, and M.-B. Naghibi-Sistani, “Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems,” Automatica, vol. 50, no. 1, pp. 193−202, 2014. doi: 10.1016/j.automatica.2013.09.043
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