Mauricio Iglesias, Miguel2; Vangsgaard, Anna Katrine1; Gernaey, Krist1; Sin, Gürkan4
1 Department of Chemical and Biochemical Engineering, Technical University of Denmark2 Center for Process Engineering and Technology, Department of Chemical and Biochemical Engineering, Technical University of Denmark3 Computer Aided Process Engineering Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark4 Centre for oil and gas – DTU, Center, Technical University of Denmark
This contribution explores the use of diagnosis and control modules based on fuzzy set theory and logic for bioreactor monitoring and control. With this aim, two independent modules were used jointly to carry out first the diagnosis of the state of the system and then use transfer this information to control the reactor. The separation in diagnosis and control allowed a more intuitive design of the membership functions and the production rules. Hence, the resulting diagnosis-control module is simple to tune, update and maintain while providing a good control performance. In particular the diagnosis-control system was designed for a complete autotrophic nitrogen removal process. The whole module is evaluated by dynamic simulation. Additionally, the diagnosis tool was demonstrated by analysis 100 days of experimental data.
Proceedings of the 12th Ifac Symposium on Computer Applications in Biotechnology, 2013, p. 205-210