Global decentralized output-feedback stabilization of large-scale stochastic high-order nonlinear systems with multi-delays-Reference-Cited by-同舟云学术

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Global decentralized output-feedback stabilization of large-scale stochastic high-order nonlinear systems with multi-delays

Published:2016-10 Issue:15 Volume:353 Page:3944-3965
ISSN:0016-0032
Container-title:Journal of the Franklin Institute
language:en
Short-container-title:Journal of the Franklin Institute

Author:

Liu Liang,Jing Xingjian,Zhang Yifan

Funder

National Natural Science Foundation of China

Program for Liaoning Excellent Talents in University

Project Funded by China Postdoctoral Science Foundation

Internal Research Grant of Hong Kong Polytechnic University

Program for Liaoning Innovative Research Team in University

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Networks and Communications,Signal Processing,Control and Systems Engineering

Reference41 articles.

1. Output feedback prescribed performance control for interconnected time-delay systems with unknown Prandtl–Ishlinskii hysteresis;Hua;J. Frankl. Inst.,2015

2. Decentralized adaptive output feedback design for large-scale nonlinear systems;Jain;IEEE Trans. Autom. Control,1997

3. Decentralized output-feedback formation control of multiple 3-DOF laboratory helicopters;Li;J. Frankl. Inst.,2015

4. Decentralized adaptive stabilization for interconnected systems with dynamic input-output and nonlinear interactions;Liu;Automatica,2010

5. Decentralized and adaptive nonlinear tracking of large-scale systems via output feedback;Jiang;IEEE Trans. Autom. Control,2000

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2. Global Fault-Tolerant Sampled-Data Control for Large-Scale Switched Time-Delay Nonlinear Systems;IEEE Systems Journal;2020-06

3. Decentralized robust adaptive output‐feedback control for a class of large‐scale stochastic time‐delay nonlinear systems with dynamic interactions;Asian Journal of Control;2020-04-21

4. Decentralized adaptive tracking control for high-order interconnected stochastic nonlinear time-varying delay systems with stochastic input-to-state stable inverse dynamics by neural networks;Transactions of the Institute of Measurement and Control;2019-03-18

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