|
已选(0)清除
条数/页： 排序方式： |
| Asynchronous learning-based output feedback sliding mode control for semi-Markov jumpsystems: A descriptor approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1358-1369
作者: Zheng Wu ; Yiyun Zhao; Fanbiao Li; Tao Yang; Yang Shi; Weihua Gui
 Adobe PDF(2638Kb) |  收藏 | 浏览/下载：7/2 | 提交时间：2024/05/22
Asynchronous switching learning-based control output feedback semi-Markovian jump systems sliding mode control (SMC) |
| A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 965-981
作者: Yong-Chao Li; Rui-Sheng Jia; Ying-Xiang Hu; Hong-Mei Sun
 Adobe PDF(10448Kb) | 收藏 | 浏览/下载：38/17 | 提交时间：2024/03/18
Crowd density estimation linear feature calibration vision transformer weakly-supervision learning |
| A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 760-781
作者: Dingxin He; HaoPing Wang; Yang Tian; Yida Guo
Adobe PDF(9812Kb) | 收藏 | 浏览/下载：63/13 | 提交时间：2024/02/19
Adaptive control input deadzone model-free control n-DOF upper-limb exoskeleton neural network |
| Fault Estimation for a Class of Markov Jump Piecewise-Affine Systems: Current Feedback Based Iterative Learning Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 418-429
作者: Yanzheng Zhu; Nuo Xu; Fen Wu; Xinkai Chen; Donghua Zhou
Adobe PDF(5104Kb) | 收藏 | 浏览/下载：43/12 | 提交时间：2024/01/23
Current feedback fault estimation iterative learning observer Markov jump piecewise-affine system |
| Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 301-328
作者: Yuchuang Tong; Haotian Liu; Zhengtao Zhang
Adobe PDF(7587Kb) | 收藏 | 浏览/下载：103/22 | 提交时间：2024/01/23
Future trends and challenges humanoid robots human-robot interaction key technologies potential applications |
| Reinforcement Learning in Process Industries: Review and Perspective 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 283-300
作者: Oguzhan Dogru; Junyao Xie; Om Prakash; Ranjith Chiplunkar; Jansen Soesanto; Hongtian Chen; Kirubakaran Velswamy; Fadi Ibrahim; Biao Huang
Adobe PDF(1275Kb) | 收藏 | 浏览/下载：46/15 | 提交时间：2024/01/23
Process control process systems engineering reinforcement learning |
| 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：263/184 | 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) |
| Magnetic Field-Based Reward Shaping for Goal-Conditioned Reinforcement Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 12, 页码: 2233-2247
作者: Hongyu Ding; Yuanze Tang; Qing Wu; Bo Wang; Chunlin Chen; Zhi Wang
Adobe PDF(5205Kb) | 收藏 | 浏览/下载：102/34 | 提交时间：2023/10/31
Dynamic environments goal-conditioned reinforcement learning magnetic field reward shaping |
| Geometry Flow-Based Deep Riemannian Metric Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1882-1892
作者: Yangyang Li; Chaoqun Fei; Chuanqing Wang; Hongming Shan; Ruqian Lu
Adobe PDF(1815Kb) | 收藏 | 浏览/下载：125/42 | 提交时间：2023/08/10
Curvature regularization deep metric learning (DML) embedding learning geometry flow riemannian metric |
| Survey on AI and Machine Learning Techniques for Microgrid Energy Management Systems 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1513-1529
作者: Aditya Joshi; Skieler Capezza; Ahmad Alhaji; Mo-Yuen Chow
Adobe PDF(4919Kb) | 收藏 | 浏览/下载：172/78 | 提交时间：2023/06/14
Consensus energy management system (EMS) reinforcement learning supervised learning |
