Guaranteed Cost Finite-Time Control of Uncertain Coupled Neural Networks
This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties are assumed to be time-varying norm bounded, which appears on the system state and input matrices. The robust guaranteed cost control laws pre...
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Published in | IEEE transactions on cybernetics Vol. 52; no. 1; pp. 481 - 494 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.01.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
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Abstract | This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties are assumed to be time-varying norm bounded, which appears on the system state and input matrices. The robust guaranteed cost control laws presented in this article include both continuous feedback controllers and intermittent feedback controllers, which were rarely found in the literature. The proposed guaranteed cost finite-time control is designed in terms of a set of linear-matrix inequalities (LMIs) to steer the coupled neural networks to achieve finite-time synchronization with an upper bound of a guaranteed cost function. Furthermore, open-loop optimization problems are formulated to minimize the upper bound of the quadratic cost function and convergence time, it can obtain the optimal guaranteed cost periodically intermittent and continuous feedback control parameters. Finally, the proposed guaranteed cost periodically intermittent and continuous feedback control schemes are verified by simulations. |
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AbstractList | This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties are assumed to be time-varying norm bounded, which appears on the system state and input matrices. The robust guaranteed cost control laws presented in this article include both continuous feedback controllers and intermittent feedback controllers, which were rarely found in the literature. The proposed guaranteed cost finite-time control is designed in terms of a set of linear-matrix inequalities (LMIs) to steer the coupled neural networks to achieve finite-time synchronization with an upper bound of a guaranteed cost function. Furthermore, open-loop optimization problems are formulated to minimize the upper bound of the quadratic cost function and convergence time, it can obtain the optimal guaranteed cost periodically intermittent and continuous feedback control parameters. Finally, the proposed guaranteed cost periodically intermittent and continuous feedback control schemes are verified by simulations. |
Author | Hu, Junhao Fan, Yuling Lu, Zhenyu Mei, Jun |
Author_xml | – sequence: 1 givenname: Jun surname: Mei fullname: Mei, Jun email: meij0000@163.com organization: School of Mathematics and Statistics, South-Central University for Nationalities, Wuhan, China – sequence: 2 givenname: Zhenyu orcidid: 0000-0002-5066-4716 surname: Lu fullname: Lu, Zhenyu email: luzhenyu76@163.com organization: School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China – sequence: 3 givenname: Junhao orcidid: 0000-0003-3538-2785 surname: Hu fullname: Hu, Junhao email: junhaohu74@163.com organization: School of Mathematics and Statistics, South-Central University for Nationalities, Wuhan, China – sequence: 4 givenname: Yuling surname: Fan fullname: Fan, Yuling email: ylfan.up@gmail.com organization: College of Informatics, Huazhong Agricultural University, Wuhan, China |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32275628$$D View this record in MEDLINE/PubMed |
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Snippet | This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties... |
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SubjectTerms | Adaptive control Algorithms Control systems Control theory Convergence Cost function Feedback Feedback control Finite-time synchronization guaranteed cost control intermittent control Linear matrix inequalities Mathematical analysis Neural networks Neural Networks, Computer Optimization Parameter uncertainty Robust control Synchronization Time synchronization uncertain coupled neural networks Upper bound Upper bounds |
Title | Guaranteed Cost Finite-Time Control of Uncertain Coupled Neural Networks |
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