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Adaptive Neural Control of Nonlinear Nonstrict Feedback Systems With Full-State Constraints: A Novel Nonlinear Mapping Method 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 9
作者:  Zhang, Jiaming;  Niu, Ben;  Wang, Ding;  Wang, Huanqing;  Duan, Peiyong;  Zong, Guangdeng
收藏  |  浏览/下载：196/0  |  提交时间：2022/01/27
Nonlinear systems  Artificial neural networks  Design methodology  Adaptive control  Time-varying systems  Fuzzy logic  Backstepping  Asymptotic tracking control  neural networks (NN)  nonlinear mapping (NM)  nonstrict feedback structure  time-varying full-state constraints  uncertain nonlinear system  
Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 8, 页码: 3658-3668
作者:  Wang, Huanqing;  Liu, Peter Xiaoping;  Li, Shuai;  Wang, Ding
收藏  |  浏览/下载：183/0  |  提交时间：2019/12/16
Adaptive neural control  backstepping  nonlower triangular nonlinear systems  output-feedback control  
Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 6, 页码: 1323-1334
作者:  Liu, Derong;  Li, Hongliang;  Wang, Ding
Adobe PDF(1114Kb)  |  收藏  |  浏览/下载：292/88  |  提交时间：2015/09/17
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Neural Networks  Neurodynamic Programming  Nonlinear Systems  Optimal Control  
Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 卷号: 25, 期号: 2, 页码: 418-428
作者:  Liu, Derong;  Wang, Ding;  Li, Hongliang
Adobe PDF(1311Kb)  |  收藏  |  浏览/下载：271/104  |  提交时间：2015/08/12
Adaptive Dynamic Programming  Decentralized Control  Large-scale Systems  Neural Networks  Nonlinear Interconnected Systems  Optimal Control  Policy Iteration  Reinforcement Learning