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Recurrent neural network inspired finite-time control design 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1527-1529
作者:  Jianan Liu;  Shihua Li;  Rongjie Liu
Adobe PDF(1176Kb)  |  收藏  |  浏览/下载:5/3  |  提交时间:2024/05/22
Fixed-Time Antidisturbance Consensus Tracking for Nonlinear Multiagent Systems with Matching and Mismatching Disturbances 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1410-1423
作者:  Xiangmin Tan;  Chunyan Hu;  Guanzhen Cao;  Qinglai Wei;  Wei Li;  Bo Han
Adobe PDF(3106Kb)  |  收藏  |  浏览/下载:5/2  |  提交时间:2024/05/22
Antidisturbance  backstepping  consensus tracking  fixed-time stability  multiagent system (MASs)  strict feedback affine nonlinear systems  
Stabilization Controller of An Extended Chained Nonholonomic System With Disturbance: An FAS Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1262-1273
作者:  Zhongcai Zhang;  Guangren Duan
Adobe PDF(2299Kb)  |  收藏  |  浏览/下载:21/6  |  提交时间:2024/04/10
Disturbance observer  exponential stabilization  finite-time stabilization  fully actuated systems  nonholonomic systems  
Nested Saturated Control of Uncertain Complex Cascade Systems Using Mixed Saturation Levels 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1163-1174
作者:  Meng Li;  Zhigang Zeng
Adobe PDF(1184Kb)  |  收藏  |  浏览/下载:22/7  |  提交时间:2024/04/10
Differentiable saturation functions  global stabilization analysis  mixed saturation levels  nested saturated control  uncertain complex cascade systems  
A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2024, 页码: 12
作者:  Qin, Shijie;  Li, Houcheng;  Cheng, Long
收藏  |  浏览/下载:42/0  |  提交时间:2024/03/27
Adaptive dynamic programming (ADP)  brain-inspired method  muscle synergy  musculoskeletal system  reinforcement learning (RL)  tracking control  
Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 982-995
作者:  Tao Wang;  Qiming Chen;  Xun Lang;  Lei Xie;  Peng Li;  Hongye Su
Adobe PDF(3095Kb)  |  收藏  |  浏览/下载:41/14  |  提交时间:2024/03/18
Convolutional neural networks (CNNs)  deep learning  image processing  oscillation detection  process industries  
Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 907-918
作者:  Xuerao Wang;  Qingling Wang;  Yanxu Su;  Yuncheng Ouyang;  Changyin Sun
Adobe PDF(3677Kb)  |  收藏  |  浏览/下载:28/12  |  提交时间:2024/03/18
Asymptotic stability  fault-tolerant control  input saturation  robust integral of the sign of error  unmanned underwater vehicle  
Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 595-607
作者:  Jianguo Zhao;  Chunyu Yang;  Weinan Gao;  Linna Zhou;  Xiaomin Liu
Adobe PDF(2409Kb)  |  收藏  |  浏览/下载:46/22  |  提交时间:2024/02/19
Adaptive optimal control  decentralized control  output regulation  reinforcement learning (RL)  singularly perturbed systems (SPSs)  
Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 131-140
作者:  Zhongyang Wang;  Youqing Wang;  Zdzisław Kowalczuk
Adobe PDF(1538Kb)  |  收藏  |  浏览/下载:150/74  |  提交时间:2024/01/02
Adaptive dynamic programming (ADP)  internal model principle (IMP)  output feedback problem  policy iteration (PI)  value iteration (VI)  
Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 18-36
作者:  Ding Wang;  Ning Gao;  Derong Liu;  Jinna Li;  Frank L. Lewis
Adobe PDF(1945Kb)  |  收藏  |  浏览/下载:257/184  |  提交时间:2024/01/02
Adaptive dynamic programming (ADP)  advanced control  complex environment  data-driven control  event-triggered design  intelligent control  neural networks  nonlinear systems  optimal control  reinforcement learning (RL)