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Receding Horizon Stabilization and Disturbance Attenuation for Neural Networks With Time-Varying Delay
- Authors
- Ahn, Choon Ki; Shi, Peng; Wu, Ligang
- Issue Date
- Dec-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
- 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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Related Researcher
- Ahn, Choon ki
- College of Engineering (School of Electrical Engineering)