Abstract
The development of dynamic models based on
physics is one of the biggest problems that real time optimization
(RTO) faces for industrial processes. In this work, we develop
a new approach by using system identification for the closedloop
dynamics in the optimization algorithm to overcome such a
problem. The identification is done by using transfer functions
and Wiener models with piece-wise linear output functions to
generate multi-model for different cases of disturbances or other
measured external inputs. These models are used to calculate
optimal references to be used in RTO. The new procedure
is applied to a continuous stirred tank reactor (CSTR). The
numerical simulations show the effectiveness of the implemented
method by comparing it with previous work from literature.
physics is one of the biggest problems that real time optimization
(RTO) faces for industrial processes. In this work, we develop
a new approach by using system identification for the closedloop
dynamics in the optimization algorithm to overcome such a
problem. The identification is done by using transfer functions
and Wiener models with piece-wise linear output functions to
generate multi-model for different cases of disturbances or other
measured external inputs. These models are used to calculate
optimal references to be used in RTO. The new procedure
is applied to a continuous stirred tank reactor (CSTR). The
numerical simulations show the effectiveness of the implemented
method by comparing it with previous work from literature.
| Originalsprache | englisch |
|---|---|
| Titel | The proceeding of the 24th International Conference on Process Control |
| Seiten | 54-59 |
| Seitenumfang | 6 |
| Publikationsstatus | Veröffentlicht - 2023 |