An Approach, Via Entropy, to the Stability of Random Large-Scale Sampled-Data Systems Under Structural Perturbations

[+] Author and Article Information
Guy Jumarie

Department of Mathematics, Université du Québec à Montréal, Montreal, Quebec, H3C 3P8 Canada

J. Dyn. Sys., Meas., Control 104(1), 49-57 (Mar 01, 1982) (9 pages) doi:10.1115/1.3149632 History: Received April 04, 1981; Online July 21, 2009


The concept of entropy in information theory is used to investigate the sensitivity and the stability of sampled-data systems in the presence of random perturbations. After a brief background on the definition, the practical meaning and the main properties of the entropy, its relations with asymptotic insensitiveness are exhibited and then some new results on the sensitivity and the stochastic stability of linear and nonlinear multivariable sampled data systems are derived. A new concept of stochastic conditional asymptotic stability is obtained which seems to be of direct application in the analysis of large-scale systems. Sufficient conditions for stability are stated. This approach provides a new look over stochastic stability. In addition, variable transformations act additively on entropy, via Jacobian determinant, and as a result the corresponding calculus is very simple.

Copyright © 1982 by ASME
Topics: Stability , Entropy
Your Session has timed out. Please sign back in to continue.





Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In