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Fixed-time observer based adaptive neural network time-varying formation tracking control for multi-agent systems via minimal learning parameter approach 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2020, 卷号: 14, 期号: 9, 页码: 1147-1157
作者:  Xiong, Tianyi;  Pu, Zhiqiang;  Yi, Jianqiang;  Tao, Xinlong
收藏  |  浏览/下载：267/0  |  提交时间：2020/07/06
neurocontrollers  multi-agent systems  Lyapunov methods  closed loop systems  nonlinear control systems  time-varying systems  adaptive control  observers  uncertain systems  position control  radial basis function networks  robust control  control system synthesis  learning (artificial intelligence)  minimal learning-parameter approach  fixed-time CLSO  time-varying formation tracking problem  formation tracking control scheme  multiagent systems  time-varying formation tracking control problem  model uncertainties  velocity measurements  radial basis function neural networks  fixed-time cascaded leader state observer  fixed-time observer-based adaptive neural network time-varying formation tracking control  RBFNN-based adaptive control scheme  
Adaptive dynamic programming for robust neural control of unknown continuous-time non-linear systems 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 14, 页码: 2307-2316
作者:  Yang, Xiong;  He, Haibo;  Liu, Derong;  Zhu, Yuanheng
浏览  |  Adobe PDF(2123Kb)  |  收藏  |  浏览/下载：422/141  |  提交时间：2017/09/13
Dynamic Programming  Robust Control  Neurocontrollers  Continuous Time Systems  Control System Synthesis  Nonlinear Control Systems  Optimal Control  Function Approximation  Monte Carlo Methods  Closed Loop Systems  Asymptotic Stability  Adaptive Dynamic Programming  Robust Neural Control Design  Unknown Continuous-time Nonlinear Systems  Ct Nonlinear Systems  Adp-based Robust Neural Control Scheme  Robust Nonlinear Control Problem  Nonlinear Optimal Control Problem  Nominal System  Adp Algorithm  Actor-critic Dual Networks  Control Policy Approximation  Value Function Approximation  Actor Neural Network Weights  Critic Nn Weights  Monte Carlo Integration Method  Closed-loop System  Asymptotically Stability  
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：399/124  |  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  
Neural-network-based online optimal control for uncertain non-linear continuous-time systems with control constraints 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2013, 卷号: 7, 期号: 17, 页码: 2037-2047
作者:  Yang, Xiong;  Liu, Derong;  Huang, Yuzhu
浏览  |  Adobe PDF(493Kb)  |  收藏  |  浏览/下载：307/83  |  提交时间：2015/08/12
Adaptive Control  Approximation Theory  Closed Loop Systems  Continuous Time Systems  Lyapunov Methods  Neurocontrollers  Nonlinear Control Systems  Optimal Control  Robust Control  Uncertain Systems  Neural Network-based Online Adaptive Optimal Control  Uncertain Nonlinear Continuous-time Systems  Control Constraints  Infinite-horizon Optimal Control Problem  Control Policy  Saturation Constraints  Identifier-critic Architecture  Hamilton-jacobi-bellman Equation Approximation  Uncertain System Dynamics  Critic Nn  Action-critic Dual Networks  Reinforcement Learning  Identifier Nn  Policy Iteration  Lyapunovaeuros Direct Method  Closed Loop System Stability