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ccession number: 20161402188589 Title: Mean-square practical stability for uncertain stochastic system with additive noise controlled by optimal feedback Authors: Mao, Dong-Hui1 Email author iheartmay@163.com; Fang, Yang-Wang1 Email author ywfang2008@sohu.com; Yang, Peng-Fei1 Email author pfyang1988@126.com; Wu, You-Li1 Email author wu-youli2014@163.com; Yong, Xiao-Ju1 Email author xjyong1987@163.com Author affiliation: 1 Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an, China Corresponding author: Mao, Dong-Hui (iheartmay@163.com) Source title: Optik Abbreviated source title: Optik Volume: 127 Issue: 13 Issue date: July 2016 Publication year: 2016 Pages: 5334-5340 Language: English ISSN: 00304026 Document type: Journal article (JA) Publisher: Elsevier GmbH Abstract: Stability concepts addressed in the framework of Lyapunov are not suitable to analyze the stability of stochastic systems with additive noise since it has no equilibrium. The mean-square practical stability is introduced to study the stability of uncertain stochastic systems with additive noise controlled by linear-quadratic optimal feedback. By using Lyapunov functional methods and the comparison principle, criteria on mean-square practical stability of stochastic systems with partially known uncertainties and norm-bounded parameter uncertainties are deduced, respectively. Some numerical examples and simulations are given to illustrate the validity of the theoretical analysis. © 2016 Elsevier GmbH. All rights reserved. Number of references: 14 Main heading: Additive noise Controlled terms: Lyapunov functions - Numerical methods - Quadratic programming - Stability - Stability criteria - Stochastic systems - System stability Uncontrolled terms: Comparison principle - Linear quadratic - Lyapunov functional method - Norm bounded parameter uncertainty - Optimal Feedback - Practical stability - Stability concepts - Uncertain stochastic systems Classification code: 703 Electric Circuits - 921 Mathematics - 921.6 Numerical Methods - 961 Systems Science DOI: 10.1016/j.ijleo.2016.02.068 Database: Compendex Compilation and indexing terms, © 2016 Elsevier Inc. |
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