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.
| Original language | English |
|---|---|
| Article number | 6999917 |
| Pages (from-to) | 2680-2692 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Cybernetics |
| Volume | 45 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2015 Dec |
Keywords
- Cost functional
- Time delay
- disturbance attenuation
- neural network
- receding horizon stabilization
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Information Systems
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering