CASIA OpenIR中国科学院自动化研究所http://ir.ia.ac.cn:802024-03-19T09:55:17Z2024-03-19T09:55:17ZAI资讯 2024年 第03期(总第119期)张桂英http://ir.ia.ac.cn:80/handle/173211/553842024-03-19T07:37:50Z2024-03-19T07:37:48Z题名: AI资讯 2024年 第03期(总第119期)
作者: 张桂英2024-03-19T07:37:48ZParameter-Free Shifted Laplacian Reconstruction for Multiple Kernel ClusteringXi WuZhenwen RenF. Richard Yuhttp://ir.ia.ac.cn:80/handle/173211/553832024-03-18T08:07:11Z2024-03-18T08:07:11Z题名: Parameter-Free Shifted Laplacian Reconstruction for Multiple Kernel Clustering
作者: Xi Wu; Zhenwen Ren; F. Richard Yu2024-03-18T08:07:11ZA Novel Trajectory Tracking Control of AGV Based on Udwadia-Kalaba ApproachRongrong YuHan ZhaoShengchao ZhenKang HuangXianmin ChenHao SunKe Shaohttp://ir.ia.ac.cn:80/handle/173211/553822024-03-18T08:07:09Z2024-03-18T08:07:09Z题名: A Novel Trajectory Tracking Control of AGV Based on Udwadia-Kalaba Approach
作者: Rongrong Yu; Han Zhao; Shengchao Zhen; Kang Huang; Xianmin Chen; Hao Sun; Ke Shao2024-03-18T08:07:09ZAttack-Resilient Distributed Cooperative Control of Virtually Coupled High-Speed Trains via Topology ReconfigurationShunyuan XiaoXiaohua GeQing Wuhttp://ir.ia.ac.cn:80/handle/173211/553812024-03-18T08:07:07Z2024-03-18T08:07:07Z题名: Attack-Resilient Distributed Cooperative Control of Virtually Coupled High-Speed Trains via Topology Reconfiguration
作者: Shunyuan Xiao; Xiaohua Ge; Qing Wu2024-03-18T08:07:07ZSynchronization of Drive-Response Networks With Delays on Time ScalesYanxia TanZhenkun Huanghttp://ir.ia.ac.cn:80/handle/173211/553802024-03-18T08:07:06Z2024-03-18T08:07:06Z题名: Synchronization of Drive-Response Networks With Delays on Time Scales
作者: Yanxia Tan; Zhenkun Huang2024-03-18T08:07:06ZPolicy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal ControlHao ZhangYan LiZhuping WangYi DingHuaicheng Yanhttp://ir.ia.ac.cn:80/handle/173211/553792024-03-18T08:07:04Z2024-03-18T08:07:04Z题名: Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control
作者: Hao Zhang; Yan Li; Zhuping Wang; Yi Ding; Huaicheng Yan2024-03-18T08:07:04ZLyapunov Conditions for Finite-Time Input-to-State Stability of Impulsive Switched SystemsTaixiang ZhangJinde CaoXiaodi Lihttp://ir.ia.ac.cn:80/handle/173211/553782024-03-18T08:07:02Z2024-03-18T08:07:02Z题名: Lyapunov Conditions for Finite-Time Input-to-State Stability of Impulsive Switched Systems
作者: Taixiang Zhang; Jinde Cao; Xiaodi Li2024-03-18T08:07:02ZSide Information-Based Stealthy False Data Injection Attacks Against Multi-Sensor Remote EstimationHaibin GuoZhong-Hua PangChao Lihttp://ir.ia.ac.cn:80/handle/173211/553772024-03-18T08:07:01Z2024-03-18T08:07:01Z题名: Side Information-Based Stealthy False Data Injection Attacks Against Multi-Sensor Remote Estimation
作者: Haibin Guo; Zhong-Hua Pang; Chao Li2024-03-18T08:07:01Z3D Localization for Multiple AUVs in Anchor-Free Environments by Exploring the Use of Depth InformationYichen LiWenbin YuXinping Guanhttp://ir.ia.ac.cn:80/handle/173211/553762024-03-18T08:06:59Z2024-03-18T08:06:59Z题名: 3D Localization for Multiple AUVs in Anchor-Free Environments by Exploring the Use of Depth Information
作者: Yichen Li; Wenbin Yu; Xinping Guan2024-03-18T08:06:59ZFinite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network ObserverChi MaDianbiao Donghttp://ir.ia.ac.cn:80/handle/173211/553752024-03-18T08:06:58Z2024-03-18T08:06:58Z题名: Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer
作者: Chi Ma; Dianbiao Dong
摘要: This paper studies the problem of time-varying formation control with finite-time prescribed performance for non-strict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities. To eliminate nonlinearities, neural networks are applied to approximate the inherent dynamics of the system. In addition, due to the limitations of the actual working conditions, each follower agent can only obtain the locally measurable partial state information of the leader agent. To address this problem, a neural network state observer based on the leader state information is designed. Then, a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region, which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time. Finally, a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.2024-03-18T08:06:58Z