文章1：《Long Duration Coverage Control of Multiple Robotic Surface Vehicles Under Battery Energy Constraints》

概述：This letter addresses long duration coverage problem of multiple robotic surface vehicles(RSVs) subject to battery energy constraints,in addition to uncertainties and disturbances. An anti-disturbance energy-aware control method is proposed for performing coverage task of RSVs. Firstly, a centroidal Voronoi tessellation(CVT) is used to optimize the partition of the given coverage area.

作者简介：Shengnan Gao, the School of Electrical and Control Engineering, North China University of Technology; the School of Marine Electrical Engineering, Dalian Maritime University.

Zhouhua Peng,the School of Marine Electrical Engineering,Dalian Maritime University; State Key Laboratory of Maritime Technology and Safety; Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships.E-mail:zhpeng@dlmu.edu.cn.

引用：Shengnan Gao,Zhouhua Peng,Haoliang Wang,Lu Liu,Dan Wang. Long Duration Coverage Control of Multiple Robotic Surface Vehicles Under Battery Energy Constraints [J]. IEEE/CAA Journal of Automatica Sinica,2024,7: 1695-1698.

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文章2：《Secure Tracking Control via Fixed-Time Convergent Reinforcement Learning for a UAV CPS》

概述：This letter is concerned with the secure tracking control problem in the unmanned aerial vehicle(UAV) system by fixed-time convergent reinforcement learning(RL). By virtue of the zero-sum game,the false data injection(FDI) attacker and secure controller are viewed as game players.

作者简介：Zhenyu Gong, the School of Automation, Northwestern Polytechnical University; the Research&Development Institute of Northwestern Polytechnical University in Shenzhen.

Feisheng Yang, the School of Automation, Northwestern Polytechnical University; the Research&Development Institute of Northwestern Polytechnical University in Shenzhen. E-mail: yangfeisheng@nwpu.edu.cn.

引用：Zhenyu Gong,Feisheng Yang. Secure Tracking Control via Fixed-Time Convergent Reinforcement Learning for a UAV CPS [J]. IEEE/CAA Journal of Automatica Sinica,2024,7: 1699-1701.

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文章3：《A Multi-AGV Routing Planning Method Based on Deep Reinforcement Learning and Recurrent Neural Network》

概述：This letter presents a multi-automated guided vehicles(AGV) routing planning method based on deep reinforcement learning(DRL)and recurrent neural network(RNN), specifically utilizing proximal policy optimization(PPO) and long short-term memory(LSTM).

作者简介：Yishuai Lin, the School of Computer Science and Technology, Xidian University. E-mail: yslin@xidian.edu.cn.

Gang Hu, the School of Computer Science and Technology, Xidian University.

引用：Yishuai Lin,Gang Hu,Liang Wang,Qingshan Li,Jiawei Zhu.A Multi-AGV Routing Planning Method Based on Deep Reinforcement Learning and Recurrent Neural Network [J] . IEEE/CAA Journal of Automatica Sinica,2024,7: 1720-1722.

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