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Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 7, 页码: 1605-1620
作者:  Yufeng Lian;  Xingtian Xiao;  Jiliang Zhang;  Long Jin;  Junzhi Yu;  Zhongbo Sun
Adobe PDF(6691Kb)  |  收藏  |  浏览/下载：36/11  |  提交时间：2024/06/07
Cooperative motion control  noise-tolerant zeroing neural network (NTZNN)  omnidirectional mobile manipulator (OMM)  repetitive motion planning  
Guaranteed Cost Attitude Tracking Control for Uncertain Quadrotor Unmanned Aerial Vehicle Under Safety Constraints 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1447-1457
作者:  Qian Ma;  Peng Jin;  Frank L. Lewis
Adobe PDF(3186Kb)  |  收藏  |  浏览/下载：26/10  |  提交时间：2024/05/22
Attitude tracking control  quadrotor unmanned aerial vehicle (QUAV)  reinforcement learning  safety constraints  uncertain disturbances  
基于全驱系统方法的高阶严反馈系统时变输出约束控制 期刊论文
自动化学报, 2024, 卷号: 50, 期号: 2, 页码: 372-385
作者:  蔡光斌;  肖永强;  胡昌华;  杨小冈;  凡永华
Adobe PDF(3709Kb)  |  收藏  |  浏览/下载：77/25  |  提交时间：2024/04/12
全驱系统方法  高阶严反馈系统  时变输出约束  非线性转换函数  自适应动态面控制  
Integrated Tracking Control of an Underwater Bionic Robot Based on Multimodal Motions 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2024, 卷号: 54, 期号: 3, 页码: 1599-1610
作者:  Wang, Jian;  Wu, Zhengxing;  Zhang, Yang;  Kong, Shihan;  Tan, Min;  Yu, Junzhi
Adobe PDF(5090Kb)  |  收藏  |  浏览/下载：99/20  |  提交时间：2024/03/27
Disturbance observer (DOB)  fuzzy system  model predictive control (MPC)  tracking control  underwater bionic robot  
Computational Experiments for Complex Social Systems: Experiment Design and Generative Explanation 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 1022-1038
作者:  Xiao Xue;  Deyu Zhou;  Xiangning Yu;  Gang Wang;  Juanjuan Li;  Xia Xie;  Lizhen Cui;  Fei-Yue Wang
Adobe PDF(7239Kb)  |  收藏  |  浏览/下载：71/17  |  提交时间：2024/03/18
Agent-based modeling  computational experiments  cyber-physical-social systems (CPSS)  generative deduction  generative experiments  meta model