EconPapers    
Economics at your fingertips  
 

Exponential stability for nonlinear fractional order sampled-data control systems with its applications

Conggui Huang, Fei Wang and Zhaowen Zheng

Chaos, Solitons & Fractals, 2021, vol. 151, issue C

Abstract: This paper investigates some topics about fractional order nonlinear systems with sampled-data. First, according to comparison principle and Laplacian transform method, sufficient conditions are derived to guarantee that the fractional order sampled-data control systems are globally and exponentially stable. Then, based on the stability results above and some properties of fractional order integral and derivative, the sampled-data controller is designed for the fractional order neural networks. Furthermore, the synchronization criteria of fractional order dynamical networks with sampled-data communications are obtained based on matrix technique and above analysis methods. Finally, three numerical examples are provided to illustrate the effectiveness of the derived results.

Keywords: Fractional order; Nonlinear system; Sampled-data control; Stabilization; Synchronization (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077921006196
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:151:y:2021:i:c:s0960077921006196

DOI: 10.1016/j.chaos.2021.111265

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().

 
Page updated 2025-03-19
Handle: RePEc:eee:chsofr:v:151:y:2021:i:c:s0960077921006196