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|Title:||Receding horizon stabilization and disturbance attenuation for neural networks with time-varying delay|
|Citation:||IEEE Transactions on Cybernetics, 2015; 45(12):2680-2692|
|Publisher:||Institute of Electrical and Electronics Engineers|
|Choon Ki Ahn, Peng Shi, and Ligang Wu|
|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∞ performance of neural networks with time-varying or time-invariant delays. Three numerical examples are provided to illustrate the effectiveness of the proposed approach.|
|Keywords:||Cost functional; disturbance attenuation; neural network; receding horizon stabilization; time delay|
|Rights:||© 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.|
|Appears in Collections:||Aurora harvest 3|
Electrical and Electronic Engineering publications
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