Cart (Loading....) | Create Account
Close category search window
 

Robust control of the output probability density functions for multivariable 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
$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)
Hong Wang ; Dept. of Paper Sci., Univ. of Manchester Inst. of Sci. & Technol., UK

This paper presents two robust solutions to the control of the output probability density function for multi-input and multi-output stochastic systems, where the purpose of control input design is to minimise the difference between the probability density function of the system output and a given one. The probability density function of the system output is approximated by a B-spline neural network with all its weights dynamically related to the control input. The measured probability density function of the system output is directly used to construct two robust control algorithms which are insensitive to the unknown input. The stability of the closed loop system are proved under certain conditions. An illustrative example is included to demonstrate the use of the developed control algorithms and desired results have been obtained

Published in:

Decision and Control, 1998. Proceedings of the 37th IEEE Conference on  (Volume:2 )

Date of Conference:

16-18 Dec 1998

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.