CASIA OpenIR

浏览/检索结果: 共9条,第1-9条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy 期刊论文
NEUROCOMPUTING, 2016, 卷号: 214, 页码: 297-306
作者:  Wang, Ding;  Liu, Derong;  Mu, Chaoxu;  Ma, Hongwen
Adobe PDF(1113Kb)  |  收藏  |  浏览/下载:360/119  |  提交时间:2017/02/14
Adaptive Dynamic Programming  Decentralized Control  Guaranteed Cost Control  Interconnected Systems  Learning Control  Neural Networks  Optimal Control  Uncertain Plant  
Neural-Network-Based Distributed Adaptive Robust Control for a Class of Nonlinear Multiagent Systems With Time Delays and External Noises 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 卷号: 46, 期号: 6, 页码: 750-758
作者:  Ma, Hongwen;  Wang, Zhuo;  Wang, Ding;  Liu, Derong;  Yan, Pengfei;  Wei, Qinglai
Adobe PDF(880Kb)  |  收藏  |  浏览/下载:341/134  |  提交时间:2016/09/30
Distributed Adaptive Robust Control  Multiagent Systems  Neural Networks (Nns)  Noises  Time Delay  
An Approximate Optimal Control Approach for Robust Stabilization of a Class of Discrete-Time Nonlinear Systems With Uncertainties 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 卷号: 46, 期号: 5, 页码: 713-717
作者:  Wang, Ding;  Liu, Derong;  Li, Hongliang;  Luo, Biao;  Ma, Hongwen
Adobe PDF(328Kb)  |  收藏  |  浏览/下载:363/110  |  提交时间:2016/04/08
Adaptive Dynamic Programming (Adp)  Generalized Hamilton-jacobi-bellman (Ghjb) Equation  Neural Networks  Optimal Control  Robust Control  Successive Approximation Method  Uncertainties  
A neural-network-based online optimal control approach for nonlinear robust decentralized stabilization 期刊论文
SOFT COMPUTING, 2016, 卷号: 20, 期号: 2, 页码: 707-716
作者:  Wang, Ding;  Liu, Derong;  Li, Hongliang;  Ma, Hongwen;  Li, Chao
Adobe PDF(837Kb)  |  收藏  |  浏览/下载:303/67  |  提交时间:2016/06/14
Adaptive Dynamic Programming  Approximate Dynamic Programming  Neural Networks  Online Optimal Control  Robust Decentralized Stabilization  Uncertain Nonlinear Systems  
Distributed control algorithm for bipartite consensus of the nonlinear time-delayed multi-agent systems with neural networks 期刊论文
NEUROCOMPUTING, 2016, 卷号: 174, 页码: 928-936
作者:  Wang, Ding;  Ma, Hongwen;  Liu, Derong
Adobe PDF(1037Kb)  |  收藏  |  浏览/下载:366/153  |  提交时间:2016/03/19
Bipartite Consensus  Distributed Control Algorithm  Multi-agent Systems  Neural Networks  Time Delays  
Online approximate solution of HJI equation for unknown constrained-input nonlinear continuous-time systems 期刊论文
INFORMATION SCIENCES, 2016, 卷号: 328, 页码: 435-454
作者:  Yang, Xiong;  Liu, Derong;  Ma, Hongwen;  Xu, Yancai
浏览  |  Adobe PDF(833Kb)  |  收藏  |  浏览/下载:387/111  |  提交时间:2016/01/18
Adaptive Dynamic Programming  Hamilton-jacobi-isaacs Equation  Input Constraint  Neural Network  Optimal Control  Reinforcement Learning  
Bipartite output consensus in networked multi-agent systems of high-order power integrators with signed digraph and input noises 期刊论文
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2016, 卷号: 47, 期号: 13, 页码: 3116-3131
作者:  Ma, Hongwen;  Liu, Derong;  Wang, Ding;  Luo, Biao
Adobe PDF(1913Kb)  |  收藏  |  浏览/下载:356/116  |  提交时间:2016/10/20
Bipartite Output Consensus  High-order  Input Noises  Networked Multi-agent Systems  Power Integrator  Signed Digraph  
Data-driven controller design for general MIMO nonlinear systems via virtual reference feedback tuning and neural networks 期刊论文
NEUROCOMPUTING, 2016, 卷号: 171, 页码: 815-825
作者:  Yan, Pengfei;  Liu, Derong;  Wang, Ding;  Ma, Hongwen
浏览  |  Adobe PDF(603Kb)  |  收藏  |  浏览/下载:507/116  |  提交时间:2016/01/18
Data-driven Control  Mimo Nonlinear Systems  Model Reference Control  Neural Networks  Virtual Reference Feedback Tuning  
Adaptive tracking control of leader-following linear multi-agent systems with external disturbances 期刊论文
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2016, 卷号: 47, 期号: 13, 页码: 3167-3179
作者:  Lin, Hanquan;  Wei, Qinglai;  Liu, Derong;  Ma, Hongwen
浏览  |  Adobe PDF(1462Kb)  |  收藏  |  浏览/下载:373/105  |  提交时间:2016/06/20
Multi-agent Systems  Leader-following  Riccati Inequalities  Adaptive Control  Stochastic Disturbances