Multiobjective nonfragile fuzzy control for nonlinear stochastic financial systems with mixed time delays

In this study, a multiobjective nonfragile control is proposed for a class of stochastic Takagi and Sugeno (T–S) fuzzy systems with mixed time delays to guarantee the optimal H2 and H∞ performance simultaneously. Firstly, based on the T–S fuzzy model, two form of nonfragile state feedback controller...

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Published in:Nonlinear analysis (Vilnius, Lithuania) Vol. 24; no. 5; pp. 696 - 717
Main Authors: Yang, Yang, Xia, Jianwei, Zhao, Jianli, Li, Xiaodi, Wang, Zhen
Format: Journal Article
Language:English
Published: Vilnius University Press 26.09.2019
Subjects:
linear matrix inequality
mixed time delays
multiobjective nonfragile control
Pareto optimal solutions
Pareto optimal solutions
multiobjective nonfragile control
mixed time delays
linear matrix inequality
ISSN:1392-5113, 2335-8963
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Abstract In this study, a multiobjective nonfragile control is proposed for a class of stochastic Takagi and Sugeno (T–S) fuzzy systems with mixed time delays to guarantee the optimal H2 and H∞ performance simultaneously. Firstly, based on the T–S fuzzy model, two form of nonfragile state feedback controllers are designed to stabilize the T–S fuzzy system, that is to say, nonfragile state feedback controllers minimize the H2 and H∞ performance simultaneously. Then, by applying T–S fuzzy approach, the multiobjective H2/H∞ nonfragile fuzzy control problem is transformed into linear matrix inequality (LMI)-constrained multiobjective problem (MOP). In addition, we efficiently solve Pareto optimal solutions for the MOP by employing LMI-based multiobjective evolution algorithm (MOEA). Finally, the validity of this approach is illustrated by a realistic design example.
AbstractList In this study, a multiobjective nonfragile control is proposed for a class of stochastic Takagi and Sugeno (T–S) fuzzy systems with mixed time delays to guarantee the optimal H2 and H∞ performance simultaneously. Firstly, based on the T–S fuzzy model, two form of nonfragile state feedback controllers are designed to stabilize the T–S fuzzy system, that is to say, nonfragile state feedback controllers minimize the H2 and H∞ performance simultaneously. Then, by applying T–S fuzzy approach, the multiobjective H2/H∞ nonfragile fuzzy control problem is transformed into linear matrix inequality (LMI)-constrained multiobjective problem (MOP). In addition, we efficiently solve Pareto optimal solutions for the MOP by employing LMI-based multiobjective evolution algorithm (MOEA). Finally, the validity of this approach is illustrated by a realistic design example.
Author Zhao, Jianli
Xia, Jianwei
Yang, Yang
Wang, Zhen
Li, Xiaodi
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  organization: Shandong University of Science and Technology
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Issue 5
Keywords Pareto optimal solutions
multiobjective nonfragile control
mixed time delays
linear matrix inequality
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SubjectTerms linear matrix inequality
mixed time delays
multiobjective nonfragile control
Pareto optimal solutions
Title Multiobjective nonfragile fuzzy control for nonlinear stochastic financial systems with mixed time delays
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