Predictive controller evaluation including non-stationary high frequency noise and outliers for batch solid substrate fermentation bioreactors

Perez-Correa, JR; Fernandez-Fernandez, M

Abstract

Optimum operation and automatic control of large-scale solid substrate fermentation (SSF) bioreactors is difficult. Though advanced control algorithms can handle most challenges encountered properly, for real-time SSF processes such controllers are expensive and time consuming to design and tune. With these considerations, advanced control algorithm tests using realistic simulations appear more appropriate. We used a phenomenological process model of an SSF pilot bioreactor, coupled with a realistic noise model, to test linear model predictive controllers. We focused on the effect noise has on the performance of the control algorithms, and how to enhance performance using a combination of low-pass (Butterworth) and outlier shaving (Hampel) filters. In simulations undertaken directly with the phenomenological model it was relatively straightforward to achieve good control performance. Nevertheless, control degraded sharply when the output of the phenomenological model was contaminated with noise using our realistic noise model, even with proper signal filtering. © 2006 Springer-Verlag.

Más información

Título según WOS: Predictive controller evaluation including non-stationary high frequency noise and outliers for batch solid substrate fermentation bioreactors
Título según SCOPUS: Predictive controller evaluation including non-stationary high frequency noise and outliers for batch solid substrate fermentation bioreactors
Título de la Revista: BIOPROCESS AND BIOSYSTEMS ENGINEERING
Volumen: 29
Número: 05-jun
Editorial: Springer
Fecha de publicación: 2006
Página de inicio: 399
Página final: 407
Idioma: English
URL: http://link.springer.com/10.1007/s00449-006-0089-5
DOI:

10.1007/s00449-006-0089-5

Notas: ISI, SCOPUS