Detalle del congreso

Autores: Zumoffen, David; Basualdo, Marta.

Resumen: In this work a new methodology for solving simultaneously the problems of optimal sensorlocation and control structure selection for large scale chemical processes is presented.Here, it is considered the need of guaranteing the best plant-wide control structure beforeanswering about which is the best sensor net able for achieving that objective. In this work itis demonstrated the importance of answer both questions as an integrated problem becauseof the strong impact in the initial investment and the future controlled process performance.Most of the previous works in this area analyze these problems as separated subjects. Here,genetic algorithms (GA) are implemented to solve integer optimization problems. They representa valuable tool for deciding the most feasible sensors network since the interactioneffect point of view. In addition, this approach uses the relative gain array (RGA) analysisallowing to avoid the expert knowledge as decision criteria for pairing variables selection.The preliminary study is done on a simplified plant model obtained by subspace identificationtechniques (4sid). The final testing is performed on the rigorous dynamic model withthe obtained plant-wide structure where the controllers tuning is performed through the internalmodel control (IMC) theory. The well-known case of the Tennessee Eastman (TE)benchmark is adopted for testing the methodology described here and compared with otherstrategies.

Tipo de reunión: Simposio.

Tipo de trabajo: Artículo Completo.

Producción: Optimal Sensor Location for Chemical Process Accounting the Best Control Configuration.

Reunión científica: 10th International Symposium on Process Systems Engineering - PSE2009.

Lugar: Salvador-Bahia-Brazil.

Institución organizadora: Universidad de San Paulo.

Publicado: Sí

Lugar publicación: Anales del congreso

Mes de reunión: 12

Año: 2009.