By Topic

A hybrid genetic algorithm for estimating the optimal time scale of linear systems approximations using Laguerre models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Sabatini, A.M. ; ARTS Lab., Scuola Superiore Sant''Anna, Pisa, Italy

We deal with the problem of finding the optimal time scale of the truncated Laguerre series using numerical search techniques. We develop a hybrid genetic algorithm (GA) to search the nonlinear, multimodal squared-error function that results from least-squares approximations of the impulse response of causal linear time-invariant stable systems. The hybrid GA incorporates a Newton-Raphson (NR) local optimizer for fast convergence to the global minimum point. The proposed method competes favorably with the pure GA in solution accuracy (the number of function evaluations being the same) and with an established gradient-directed optimization algorithm in number of function evaluations (the solution accuracy being the same)

Published in:

Automatic Control, IEEE Transactions on  (Volume:45 ,  Issue: 5 )