中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
自动化研究所 [4]
采集方式
OAI收割 [4]
内容类型
期刊论文 [4]
发表日期
2020 [1]
2017 [2]
2013 [1]
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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
OAI收割
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:47/0
  |  
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
OAI收割
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
  |  
收藏
  |  
浏览/下载:34/0
  |  
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
OAI收割
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 7, 页码: 915-922
作者:
Shi, Guang
;
Liu, Derong
  |  
收藏
  |  
浏览/下载:19/0
  |  
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
OAI收割
IET CONTROL THEORY AND APPLICATIONS, 2013, 卷号: 7, 期号: 17, 页码: 2037-2047
作者:
Yang, Xiong
收藏
  |  
浏览/下载:30/0
  |  
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