Abstract
Abstract—This paper investigates data-driven, Linear-
Parameter-Varying (LPV) modeling of a high-purity distillation
column. Two LPV modeling approaches are studied: a local
approach, corresponding to the interpolation of Linear Time-
Invariant (LTI) models identified at steady-state purity levels,
and a global Least-Square Support Vector Machine (LSSVM)
approach which offers non-parametric estimation of the
system w.r.t. data with varying operating conditions. In an
extensive simulation study, it is observed that the global LSSVM
approach outperforms the local methodology in capturing
the dynamics of the high-purity distillation column under
study. The simulation results suggest that the global LS-SVM
approach provides a reliable modeling tool under realistic noise
conditions.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the European Control Conference, 17-19 July 2013, Zurich, Switzerland |
| Place of Publication | Zurich |
| Pages | 3776-3783 |
| Publication status | Published - 2013 |
| Event | 12th European Control Conference, ECC 2013 - Zurich, Switzerland, Zürich, Switzerland Duration: 17 Jul 2013 → 19 Jul 2013 Conference number: 12 http://www.ecc2013.ethz.ch/ |
Conference
| Conference | 12th European Control Conference, ECC 2013 |
|---|---|
| Abbreviated title | ECC 2013 |
| Country/Territory | Switzerland |
| City | Zürich |
| Period | 17/07/13 → 19/07/13 |
| Other | European Control Conference 2013 |
| Internet address |