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Receding Horizon Stabilization and Disturbance Attenuation for Neural Networks With Time-Varying Delay

Authors
Ahn, Choon KiShi, PengWu, Ligang
Issue Date
12월-2015
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Cost functional; disturbance attenuation; neural network; receding horizon stabilization; time delay
Citation
IEEE TRANSACTIONS ON CYBERNETICS, v.45, no.12, pp.2680 - 2692
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON CYBERNETICS
Volume
45
Number
12
Start Page
2680
End Page
2692
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/91686
DOI
10.1109/TCYB.2014.2381604
ISSN
2168-2267
Abstract
This paper is concerned with the problems of receding horizon stabilization and disturbance attenuation for neural networks with time-varying delay. New delay-dependent conditions on the terminal weighting matrices of a new finite horizon cost functional for receding horizon stabilization are established for neural networks with time-varying or time-invariant delays using single- and double-integral Wirtinger-type inequalities. Based on the results, delay-dependent sufficient conditions for the receding horizon disturbance attenuation are given to guarantee the infinite horizon H-infinity performance of neural networks with time-varying or time-invariant delays. Three numerical examples are provided to illustrate the effectiveness of the proposed approach.
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공과대학 (전기전자공학부)
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