Optimized PID controller for an industrial biological fermentation process. (November 2018)

• Record Type: Journal Article
• Authors: Khan, Omar; Madhuranthakam, Chandra Mouli R.; Douglas, Peter; Lau, Heron; Sun, Jacob; Farrell, Patrick
• Is Part Of: Journal of process control. Volume 71(2018)
• Page Start: 75
• Page End: 89
• Publication Date: 2018-11
• Subjects: PID controllers -- Transfer function models -- Tuning -- Dynamic optimization -- Fermentation; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2018.09.007
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: This paper designs a method to optimize the PID settings in a microbial fermenter. Best-fit process models are obtained and the PID parameters are dynamically optimized. Optimal settings are found for both set-point tracking and disturbance rejection. The PID optimization algorithm is demonstrated to work successfully in experiments. Abstract: Vaccine development comprises multiple stages, the first of which involves cultivating an organism in a microbial fermenter to produce a vaccine product. In order to ensure the optimal synthesis of the vaccine product, it is necessary to maintain adequate control of the dissolved oxygen (dO2 ), which is required for the organism to grow and survive. Our work is concerned with controlling the dissolved oxygen in a biological fermenter using a PID (Proportional-Integral-Derivative) Controller. The product from this fermenter is used to create the immunization for a medical illness. However, the present configuration of the PID Controller is inadequate for maintaining the dissolved oxygen at the desired level of 35% relative to saturation. This inadequacy results in violent dO2 oscillations which compromise the quality of the product. To solve this issue, we use open-loop experimental data to develop empirical transfer-function models of the control process for dissolved oxygen. Then, we apply an optimization algorithm for the PID Controller to obtain the proportional, integral, and derivative gains that would best regulate the dissolved oxygen in the fermenter. The parameters obtained from this algorithm are applied experimentally to the biological fermenter set-up and the results are used to demonstrate that the PID optimization algorithm provides controller settings which successfully regulate the dissolved oxygen.