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 11
Issue 12
IEEE/CAA Journal of Automatica Sinica
| Citation: | Z. Li, Y. Guo, G. Wang, and W. Chen, “Level curve tracking via robust RL-guided model predictive control,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 12, pp. 2512–2514, Dec. 2024. doi: 10.1109/JAS.2024.124350
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| [1] |
C. Mellucci, P. P. Menon, C. Edwards, and P. G. Challenor, “Environmental feature exploration with a single autonomous vehicle,” IEEE Trans. Control Syst. Technol., vol. 28, no. 4, pp. 1349–1362, Jul. 2019.
|
| [2] |
P. Sun, S. Li, B. Zhu, Z. Zuo, and X. Xia, “Vision-based fixed-time uncooperative aerial target tracking for UAV,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp. 1322–1324, May 2023. doi: 10.1109/JAS.2023.123510
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| [3] |
Y. Li, X. Wang, J. Sun, G. Wang, and J. Chen, “Data-driven consensus control of fully distributed event-triggered multi-agent systems,” Sci. CHINA Inf. Sci., vol. 66, no. 5, p. 152202, Feb. 2023. doi: 10.1007/s11432-022-3629-1
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| [4] |
Z. Li, K. You, and S. Song, “AUV based source seeking with estimated gradients,” J. Syst. Sci. Complex., vol. 31, no. 1, pp. 262–275, Jan. 2018. doi: 10.1007/s11424-018-7373-8
|
| [5] |
C. Xu, J. Rong, Y. Chen, H. Wu, and S. Duan, “Spatial-temporal fusion based path planning for source seeking in wireless sensor network,” Int. J. Wireless Inf. Netw., vol. 29, pp. 1–13, Nov. 2022. doi: 10.1007/s10776-021-00540-9
|
| [6] |
S. Cheng and D. A. Paley, “Optimal guidance and estimation of a 2D diffusion-advection process by a team of mobile sensors,” Automatica, vol. 137, p. 110112, Mar. 2022. doi: 10.1016/j.automatica.2021.110112
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| [7] |
L. Brinón-Arranz, L. Schenato, and A. Seuret, “Distributed source seeking via a circular formation of agents under communication constraints,” IEEE Trans. Control Netw. Syst., vol. 3, no. 2, pp. 104–115, Feb. 2016. doi: 10.1109/TCNS.2015.2428391
|
| [8] |
X. Wang, J. Sun, G. Wang, F. Allgöwer, and J. Chen, “Data-driven control of distributed event-triggered network systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 351–364, Feb. 2023. doi: 10.1109/JAS.2023.123225
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| [9] |
Z. Li, K. You, and S. Song, “Cooperative source seeking via networked multi-vehicle systems,” Automatica, vol. 115, p. 108853, 2020. doi: 10.1016/j.automatica.2020.108853
|
| [10] |
F. Dong and K. You, “The isoline tracking in unknown scalar fields with concentration feedback,” Automatica, vol. 133, p. 109779, Sept. 2021. doi: 10.1016/j.automatica.2021.109779
|
| [11] |
A. S. Matveev, A. A. Semakova, and A. V. Savkin, “Tight circumnavigation of multiple moving targets based on a new method of tracking environmental boundaries,” Automatica, vol. 79, pp. 52–60, May 2017. doi: 10.1016/j.automatica.2017.01.041
|
| [12] |
A. Matveev, I. Berman, A. Bugrova, M. Bystramovich, A. Kapitonov, and V. Manaenko, “Non-gradient based tracking of environmental field isolines in a changing medium by Dubins-vehicle type robots,” IEEE Trans. Autom. Control, vol. 69, no. 2, pp. 952–967, Feb. 2024. doi: 10.1109/TAC.2023.3284595
|
| [13] |
J. B. Rawlings, “Tutorial overview of model predictive control,” IEEE Control Syst. Mag., vol. 20, no. 3, pp. 38–52, Jun. 2000. doi: 10.1109/37.845037
|
| [14] |
W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen, “Data-driven resilient predictive control under denial-of-service,” IEEE Trans. Autom. Control, vol. 68, no. 8, pp. 4722–4737, Aug. 2023. doi: 10.1109/TAC.2022.3209399
|
| [15] |
Z. Feng, G. Cao, K. M. Grigoriadis, and Q. Pan, “Secure MPC-based path-following for UAS in adverse network environment,” IEEE Trans. Ind. Inform., vol. 19, no. 11, pp. 11091–11101, Nov. 2023. doi: 10.1109/TII.2022.3232772
|
| [16] |
H. Wei and Y. Shi, “MPC-based motion planning and control enables smarter and safer autonomous marine vehicles: Perspectives and a tutorial survey,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 1, pp. 8–24, Jan. 2023. doi: 10.1109/JAS.2022.106016
|
| [17] |
J. Zhu, H. Zhang, S. Zhao, and W. Bao, “Multi-constrained intelligent gliding guidance via optimal control and DQN,” Sci. CHINA Inf. Sci., vol. 66, no. 3, p. 132202, Mar. 2023. doi: 10.1007/s11432-022-3543-4
|
| [18] |
L. Wang, K. Wang, C. Pan, W. Xu, N. Aslam, and L. Hanzo, “Multi-agent deep reinforcement learning-based trajectory planning for multi-UAV assisted mobile edge computing,” IEEE Trans. Cogn. Commun. Netw., vol. 7, no. 1, pp. 73–84, Jan. 2020.
|
| [19] |
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine, “Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,” in Proc Int. Conf. Mach. Learn., Stockholm, Sweden, 2018, pp. 1861–1870.
|
| [20] |
M. Idrissi and F. Annaz, “Dynamic modelling and analysis of a quadrotor based on selected physical parameters,” Int. J. Mech. Eng. Rob. Res., vol. 9, no. 6, pp. 784–790, Jun. 2020.
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