Process Systems Engineering
Nonlinear stochastic modeling to improve state estimation in process monitoring and control
Version of Record online: 25 MAY 2010
Copyright © 2010 American Institute of Chemical Engineers (AIChE)
Volume 57, Issue 4, pages 996–1007, April 2011
How to Cite
Lima, F. V. and Rawlings, J. B. (2011), Nonlinear stochastic modeling to improve state estimation in process monitoring and control. AIChE J., 57: 996–1007. doi: 10.1002/aic.12308
- Issue online: 10 MAR 2011
- Version of Record online: 25 MAY 2010
- Manuscript Revised: 27 APR 2010
- Manuscript Received: 4 DEC 2009
- NSF. Grant Number: CNS-0540147
- PRF. Grant Number: 43321-AC9
- ExxonMobil Chemical Company through the Texas-Wisconsin-California Control Consortium (TWCCC)
Options for accessing this content:
- If you are a society or association member and require assistance with obtaining online access instructions please contact our Journal Customer Services team.
- If your institution does not currently subscribe to this content, please recommend the title to your librarian.
- Login via other institutional login options http://onlinelibrary.wiley.com/login-options.
- You can purchase online access to this Article for a 24-hour period (price varies by title)
- If you already have a Wiley Online Library or Wiley InterScience user account: login above and proceed to purchase the article.
- New Users: Please register, then proceed to purchase the article.
Login via OpenAthens
Search for your institution's name below to login via Shibboleth.
Registered Users please login:
- Access your saved publications, articles and searches
- Manage your email alerts, orders and subscriptions
- Change your contact information, including your password
Please register to:
- Save publications, articles and searches
- Get email alerts
- Get all the benefits mentioned below!