Back to Search
Start Over
Robust disturbance modeling for model predictive control with application to multivariable ill-conditioned processes
- Source :
-
Journal of Process Control . Dec2003, Vol. 13 Issue 8, p693. 9p. - Publication Year :
- 2003
-
Abstract
- In this paper the disturbance model, used by MPC algorithms to achieve offset-free control, is optimally designed to enhance the robustness of single-model predictive controllers. The proposed methodology requires the off-line solution of a min-max optimization problem in which the disturbance model is chosen to guarantee the best closed-loop performance in the worst case of plant in a given uncertainty region. Application to a well-known ill-conditioned distillation column is presented to show that, for ill-conditioned processes, the use of a disturbance model that adds the correction term to the process inputs guarantees a robust performance, while the disturbance model that adds the correction term to the process outputs (used by industrial MPC algorithms) does not. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 09591524
- Volume :
- 13
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Journal of Process Control
- Publication Type :
- Academic Journal
- Accession number :
- 10805493
- Full Text :
- https://doi.org/10.1016/S0959-1524(02)00134-8