中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共8条，第1-8条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Optimal control for discrete-time systems with actuator saturation 期刊论文
OPTIMAL CONTROL APPLICATIONS & METHODS, 2017, 卷号: 38, 期号: 6, 页码: 1071-1080
作者:  Lin, Qiao;  Wei, Qinglai;  Zhao, Bo
浏览  |  Adobe PDF(348Kb)  |  收藏  |  浏览/下载：521/255  |  提交时间：2017/05/04
Approximate Dynamic Programming  Discrete Time  Generalized Policy Iteration  Optimal Control  Saturating Actuators  
Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3417-3428
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
浏览  |  Adobe PDF(1068Kb)  |  收藏  |  浏览/下载：416/110  |  提交时间：2018/03/03
H-infinity Control  Adaptive Systems  Adaptive/approximate Dynamic Programming  Critic Network  Event-based Design  Learning Criterion  Neural Control  
Event-Based Constrained Robust Control of Affine Systems Incorporating an AdaptiveCritic Mechanism 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 卷号: 47, 期号: 7, 页码: 1602-1612
作者:  Wang, Ding;  Mu, Chaoxu;  Yang, Xiong;  Liu, Derong
Adobe PDF(1062Kb)  |  收藏  |  浏览/下载：306/95  |  提交时间：2017/09/12
Adaptive Critic Mechanism (Acm)  Event-based Control  Input Constraints  Nonlinear Systems  Robust Control  
Online identifier-actor-critic algorithm for optimal control of nonlinear systems 期刊论文
OPTIMAL CONTROL APPLICATIONS & METHODS, 2017, 卷号: 38, 期号: 3, 页码: 317-335
作者:  Lin, Hanquan;  Wei, Qinglai;  Liu, Derong
浏览  |  Adobe PDF(2888Kb)  |  收藏  |  浏览/下载：270/72  |  提交时间：2017/07/18
Adaptive Dynamic Programming  Optimal Control  Discrete-time  Nonlinear System  Neural Network  Online Learning  Lyapunov Method  
Echo state network-based Q-learning method for optimal battery control of offices combined with renewable energy 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 7, 页码: 915-922
作者:  Shi, Guang;  Liu, Derong;  Wei, Qinglai
浏览  |  Adobe PDF(3253Kb)  |  收藏  |  浏览/下载：408/125  |  提交时间：2017/02/23
Recurrent Neural Nets  Neurocontrollers  Learning (Artificial Intelligence)  Office Environment  Optimal Control  Solar Power  Energy Consumption  Time Series  Secondary Cells  Energy Management Systems  Function Approximation  Echo State Network-based Q-learning Method  Optimal Battery Control  Renewable Energy  Optimal Energy Management  Solar Energy  Energy Consumption  Energy Demand  Time Series  Real-time Electricity Rate  Periodic Functions  Q-function  Optimal Charging Strategy  Optimal Discharging Strategy  Optimal Idle Strategy  Numerical Analysis  
Adaptive near-optimal controllers for non-linear decentralised feedback stabilisation problems 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 6, 页码: 799-806
作者:  Wang, Ding;  He, Haibo;  Zhao, Bo;  Liu, Derong
Adobe PDF(3178Kb)  |  收藏  |  浏览/下载：324/93  |  提交时间：2017/07/18
Adaptive Control  Optimal Control  Continuous Time Systems  Nonlinear Control Systems  Decentralised Control  Feedback  Stability  Control System Synthesis  Adaptive-critic-based Near-optimal Controller  Continuous-time Nonlinear Decentralised Feedback Stabilisation Problem  Decentralised Feedback Control Problem  Updating Rule  Approximation Property  Learning Mechanism  
A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm 期刊论文
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2017, 卷号: 48, 期号: 3, 页码: 525-534
作者:  Lin, Qiao;  Wei, Qinglai;  Liu, Derong
浏览  |  Adobe PDF(296Kb)  |  收藏  |  浏览/下载：314/130  |  提交时间：2017/02/14
Adaptive Dynamic Programming  Affine Nonlinear Systems  Discrete-time  Generalised Policy Iteration  Neural Network  Tracking Control  
Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 卷号: 27, 期号: 2, 页码: 444-458
作者:  Wei, Qinglai;  Song, Ruizhuo;  Yan, Pengfei
浏览  |  Adobe PDF(2204Kb)  |  收藏  |  浏览/下载：400/137  |  提交时间：2016/06/14
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Neurodynamic Programming  Nonlinear Systems  Optimal Control  Recurrent Neural Network (Rnn)  Reinforcement Learning