Two-stage continuous biomethane production from enzymatic hydrolysate of agave bagasse: Modelling, identification and control. (December 2022)

• Record Type: Journal Article
• Authors: Calderón-Soto, Luis F.; López-Gutiérrez, Irma; Valencia-Ojeda, Casandra; Aguilar-López, Ricardo; Alatriste-Mondragón, Felipe; Femat, Ricardo
• Is Part Of: Journal of process control. Volume 120(2022)
• Page Start: 14
• Page End: 27
• Publication Date: 2022-12
• Subjects: Biomethane optimization -- Enzymatic hydrolysation -- Modelling and robust feedback control -- Experimental proof-of-concept; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2022.10.007
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: An AM2 model modification is proposed by including the parameter identification and a robust feedback control synthesis. The contribution is shown by experimental proof-of-concept. The AM2 model is modified with the aim of including the CODs changes in the effluent near the steady state with the inlet CODt concentration changes at a fixed flow rate. The parameter identification is experimentally implemented on-line and computationally performed via the Levenberg–Marquardt algorithm. To this end, an experimental set-up was carried out each from a two-stage biomethane production process stage as an instrumented and automated bioreactor. Afterward, robust feedback control is implemented for each stage. For the first stage, the VFA productivity maximum is defined as the control goal whereas the biomethane maximum flow is the aim on the second stage. The feedback control is robust against kinetics and parametric uncertainties such that the biogas production reaches biomethane maximum production. In this sense, the contribution shows the biomethane production can be optimized through enzymatic agave bagasse hydrolysate. Highlights: Biogas yielding via enzymatic hydrolysate of agave bagasse needs model modification. A modified model renders an accurate structure for kinetics parameter identification. A robust feedback control allows us to enhance the biomethane production. An experimental benchmark shows the concept of enhancing biomethane production.