Abstract
This paper presents a novel data-based controller design for nonlinear systems based on the VRFT design framework and block-oriented modeling. Identification of a complete dynamic model of the nonlinear system is not required, whereas only the static nonlinearity has to be estimated. Moreover, the nonlinearity estimation and the controller design are performed simultaneously without the needs of iterative procedures or nonlinear optimization. Simulation studies of a distillation column and a pH neutralization process confirms the effectiveness of the proposed design method.
| Original language | English |
|---|---|
| Title of host publication | Computer Aided Chemical Engineering |
| Publisher | Elsevier B.V. |
| Pages | 1691-1696 |
| Number of pages | 6 |
| DOIs | |
| State | Published - 2015 |
Publication series
| Name | Computer Aided Chemical Engineering |
|---|---|
| Volume | 37 |
| ISSN (Print) | 1570-7946 |
Bibliographical note
Publisher Copyright:© 2015 Elsevier B.V.
Keywords
- Hammerstein system
- Nonlinear process control
- VRFT
- Wiener system
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