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面向工业过程的图像生成及其应用研究综述 期刊论文
自动化学报, 2024, 卷号: 50, 期号: 2, 页码: 211-240
作者:  汤健;  郭海涛;  夏恒;  王鼎;  乔俊飞
Adobe PDF(6988Kb)  |  收藏  |  浏览/下载:9/2  |  提交时间:2024/04/12
工业过程  视觉感知  图像生成  生成图像评估与应用  城市固废焚烧  
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:230/179  |  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)  
Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 7, 页码: 1262-1272
作者:  Mingming Ha;  Ding Wang;  Derong Liu
Adobe PDF(1832Kb)  |  收藏  |  浏览/下载:190/64  |  提交时间:2022/06/27
Adaptive critic design  adaptive dynamic programming (ADP)  approximate dynamic programming  discrete-time nonlinear systems  reinforcement learning  stability analysis  tracking control  value iteration (VI)  
Improved value iteration for neural-network-based stochastic optimal control design 期刊论文
NEURAL NETWORKS, 2020, 卷号: 124, 页码: 280-295
作者:  Liang, Mingming;  Wang, Ding;  Liu, Derong
Adobe PDF(5875Kb)  |  收藏  |  浏览/下载:219/50  |  提交时间:2020/06/02
Adaptive critic designs  Adaptive dynamic programming  Neural networks  Optimal control  Stochastic processes  Value iteration  
Neuro-optimal control for discrete stochastic processes via a novel policy iteration algorithm 期刊论文
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 卷号: 50, 期号: 11, 页码: 3972-3985
作者:  Liang, Mingming;  Wang, Ding;  Liu, Derong
浏览  |  Adobe PDF(1604Kb)  |  收藏  |  浏览/下载:173/63  |  提交时间:2020/10/23
Adaptive critic designs  adaptive dynamic programming (ADP)  local policy iteration  neuro-dynamic programming  optimal control  stochastic processes  
A novel neural optimal control framework with nonlinear dynamics: Closed-loop stability and simulation verification 期刊论文
NEUROCOMPUTING, 2017, 卷号: 266, 页码: 353-360
作者:  Wang, Ding;  Mu, Chaoxu
Adobe PDF(1503Kb)  |  收藏  |  浏览/下载:295/62  |  提交时间:2018/03/03
Adaptive Dynamic Programming  Adaptive System  Learning Control  Neural Network  Optimal Regulator  Stability  
Adaptive tracking control for a class of continuous-time uncertain nonlinear systems using the approximate solution of HJB equation 期刊论文
NEUROCOMPUTING, 2017, 卷号: 260, 页码: 432-442
作者:  Mu, Chaoxu;  Sun, Changyin;  Wang, Ding;  Song, Aiguo
Adobe PDF(1555Kb)  |  收藏  |  浏览/下载:411/157  |  提交时间:2017/09/12
Adaptive Tracking Control  Hamilton-jacobi-bellman (Hjb) Equation  Adaptive Dynamic Programming (Adp)  Neural Networks  Uncertainties  
Adaptive Critic Nonlinear Robust Control: A Survey 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3429-3451
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
Adobe PDF(1954Kb)  |  收藏  |  浏览/下载:401/142  |  提交时间:2018/03/03
Adaptive Critic Designs  Adaptive/approximate Dynamic Programming (Adp)  Boundedness  Convergence  Neural Networks  Optimal Control  Reinforcement Learning  Robust Control  Stability  
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3341-3354
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning;  Wang, Ding;  Lewis, Frank L.
Adobe PDF(3217Kb)  |  收藏  |  浏览/下载:563/204  |  提交时间:2016/11/09
Adaptive Control  Adaptive Dynamic Programming (Adp)  Data-based  Off-policy Learning  Optimal Control  Policy Gradient  
Event-Driven Nonlinear Discounted Optimal Regulation Involving a Power System Application 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 卷号: 64, 期号: 10, 页码: 8177-8186
作者:  Wang, Ding;  He, Haibo;  Zhong, Xiangnan;  Liu, Derong
浏览  |  Adobe PDF(1126Kb)  |  收藏  |  浏览/下载:337/111  |  提交时间:2018/03/03
Adaptive/approximate Dynamic Programming  Approximation  Discount Factor  Event-driven Control  Neural Networks  Optimal Regulation  Power System