By Topic

Minimum entropy control for non-linear and non-Gaussian two-input and two-output dynamic stochastic systems

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
$33 $33
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

3 Author(s)
J. Zhang ; State Key Lab. of Alternate Electr. Power Syst. with Renewable Energy Sources, North China Electr. Power Univ., Beijing, China ; M. Ren ; H. Wang

In this study, the problem of control algorithm design for a class of nonlinear two-input and two-output systems with non-Gaussian disturbances is investigated, where a general non-linear auto-regressive moving average with exogenous model is used to describe the system. Based on the deduced probability density functions of tracking errors, a new performance index is established using the entropy and joint entropy so as to characterise the uncertainty of the tracking errors of the closed-loop system. This performance also includes the expectations of tracking errors and the constrains of control energy. A recursive optimisation control algorithm is obtained by minimising the performance index. Moreover, the local stability condition of the closed-loop systems is established after some formulations. Finally, the comparative simulation results are presented to show that the performance of the proposed algorithm is superior to that of proportional-integral-derivative controller.

Published in:

IET Control Theory & Applications  (Volume:6 ,  Issue: 15 )