Title :
Receding Horizon Stabilization and Disturbance Attenuation for Neural Networks With Time-Varying Delay
Author :
Choon Ki Ahn ; Peng Shi ; Ligang Wu
Author_Institution :
Sch. of Electr. Eng., Korea Univ., Seoul, South Korea
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 :
H∞ control; delay systems; infinite horizon; integral equations; neurocontrollers; stability; time-varying systems; delay-dependent condition; delay-dependent sufficient condition; double-integral Wirtinger-type inequalities; finite horizon cost functional; infinite horizon H∞ performance; neural network; receding horizon disturbance attenuation; receding horizon stabilization; single-integral Wirtinger-type inequalities; terminal weighting matrices; time-invariant delay; time-varying delay; Attenuation; Biological neural networks; Delay effects; Delays; Linear matrix inequalities; Symmetric matrices; Cost functional; disturbance attenuation; neural network; receding horizon stabilization; time delay;
Journal_Title :
Cybernetics, IEEE Transactions on
DOI :
10.1109/TCYB.2014.2381604
