Control of an anaerobic bioreactor using a fuzzy supervisory controller. (July 2021)

• Record Type: Journal Article
• Authors: Ghanavati, Mohammad Amin; Vafa, Ehsan; Shahrokhi, Mohammad
• Is Part Of: Journal of process control. Volume 103(2021)
• Page Start: 87
• Page End: 99
• Publication Date: 2021-07
• Subjects: Anaerobic digestion -- Adaptive model predictive control -- Fuzzy supervisory control; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2021.05.010
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: In the present work, a fuzzy supervisory control approach combined with an adaptive model predictive controller (AMPC), has been proposed to maximize the productivity of an anaerobic digestion (AD) process, while keeping the operation stable. In the proposed hierarchal control strategy, the set-point of the inner loop is provided by a supervisory controller. In the inner loop an AMPC has been applied to achieve the desired methane production rate by manipulating the feed flow rate. The AMPC is designed based on the auto-regressive moving average (ARMA) model whose parameters are updated at each sampling time to make the controller more robust against uncertainties and external loads. In the supervisory level, a fuzzy logic system is utilized to adjust the set-point of the lower level controller based on the measurement of total concentration of the volatile fatty acids (VFA). To prevent VFA accumulation, an override control strategy is used to bring the total VFA concentration to its safe level when it exceeds a predetermined level. To simulate the AD process, the well-established Anaerobic Digestion Model No.1 (ADM1) has been used. Through simulation study, the performance of the proposed control strategy has been evaluated. Simulation results indicate that the proposed control strategy could maximize the methane production rate in presence of different external disturbances and model mismatch. Highlights: Applying a supervisory fuzzy controller to an anaerobic bioreactor. Keeping methane production rate near its optimal value under different operation conditions. Using the override control strategy to keep the reactor stable against severe external disturbances.