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Sliding-Mode Surface-Based Approximate Optimal Control for Uncertain Nonlinear Systems With Asymptotically Stable Critic Structure 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 卷号: 51, 期号: 6, 页码: 2858-2869
作者:  Zhao, Bo;  Liu, Derong;  Alippi, Cesare
收藏  |  浏览/下载：225/0  |  提交时间：2021/08/15
Optimal control  Perturbation methods  Nonlinear systems  Uncertainty  Cost function  Stability analysis  Adaptive systems  Adaptive critic designs  adaptive dynamic programming (ADP)  optimal control  sliding mode surface (SMS)  unknown mismatched perturbations  
Continuous-Time Time-Varying Policy Iteration 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 12, 页码: 4958-4971
作者:  Wei, Qinglai;  Liao, Zehua;  Yang, Zhanyu;  Li, Benkai;  Liu, Derong
Adobe PDF(3149Kb)  |  收藏  |  浏览/下载：273/50  |  提交时间：2021/03/02
Optimal control  Nonlinear systems  Time-varying systems  Mathematical model  Dynamic programming  Approximation algorithms  Iterative algorithms  Adaptive critic designs  adaptive dynamic programming (ADP)  neuro-dynamic programming  nonlinear systems  optimal control  policy iteration  
Reinforcement Learning-Based Optimal Stabilization for Unknown Nonlinear Systems Subject to Inputs With Uncertain Constraints 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 4330-4340
作者:  Zhao, Bo;  Liu, Derong;  Luo, Chaomin
收藏  |  浏览/下载：212/0  |  提交时间：2021/01/07
Nonlinear systems  Optimal control  Artificial neural networks  Actuators  Observers  Feedforward systems  Adaptive dynamic programming (ADP)  neural networks (NNs)  optimal control  reinforcement learning (RL)  uncertain input constraints  unknown nonlinear systems  
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：201/67  |  提交时间：2020/10/23
Adaptive critic designs  adaptive dynamic programming (ADP)  local policy iteration  neuro-dynamic programming  optimal control  stochastic processes  
Adaptive Q-Learning for Data-Based Optimal Output Regulation With Experience Replay 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 12, 页码: 3337-3348
作者:  Luo, Biao;  Yang, Yin;  Liu, Derong
收藏  |  浏览/下载：299/0  |  提交时间：2019/01/08
Data-based  experience replay  neural networks (NNs)  off-policy  optimal control  Q-learning (QL)