Abstract
In this paper, a novel control algorithm to increase biohydrogen production in a continuous reactor using the sulphate-reducing bacteria Desulfovibrio alaskensis with lactate as carbon source is proposed. This work was conducted via numerical simulations, based on an experimentally corroborated kinetic model, considered as a benchmark of the system. A bifurcation analysis to identify the reactor’s steady-state performance was done in order to identify feasible operating regions. The proposed controller cancels the upper bounds of the reactor, imposing a finite-time convergence to the selected set point. The closed-loop stability of the reactor is analysed via the dynamic of the regulation error. Finally, numerical experiments were conducted in order to compare the dynamic behaviour of the proposed closed-loop system versus its open-loop counterpart and a well-tuned classical PI controller one. The proposed methodology increases the hydrogen productivity controlling with a satisfactory performance the biomass concentration, which is considered as the control output.
Acknowledgment
H.I. Velázquez-Sánchez is very grateful with CONACyT for the financial support via a postgraduate scholarship and with CINVESTAV-IPN for supplying the research facilities to develop this work.
Nomenclature
| Symbol | Description | Units |
| µmax | Maximum bacterial specific growth rate | h–1 |
| Ac | Acetate concentration into the reactor | mg L–1 |
| e | Absolute estimation error | ---- |
| H | Hydrogen concentration into the reactor | mL L–1 |
| k1 | Proportional gain of the proposed controller | ---- |
| k2 | Proposed controller tuning variable | ---- |
| Kd | Cell death constant | h–1 |
| Kis | Levenspiel’s product inhibition constant | mg L–1 |
| klac | Lactate affinity constant for biomass growth | mg L–1 |
| klh | Lactate affinity constant for hydrogen production | mg L–1 |
| Ks | Substrate affinity constant | mg L–1 |
| Lac | Lactate concentration into the reactor | mg L–1 |
| Lacin | Lactate concentration of the feeding solution | mg L–1 |
| m | Proposed controller tuning variable | ---- |
| n | Levenspiel’s product inhibition exponent | ---- |
| rmax | Maximum specific hydrogen production rate | mg L–1 h–1 |
| S- | Sulfide concentration into the reactor | mg L–1 |
| SO | Sulphate concentration into the reactor | mg L–1 |
| SOin | Sulphate concentration of the feeding solution | mg L–1 |
| X | Biomass concentration | mg L–1 |
| Y1 | Biomass yield over lactate | mg mg–1 |
| Y2 | Biomass yield over sulphate | mg mg–1 |
| Y3 | Sulfide yield over biomass | mg mg–1 |
| Y4 | Acetate yield over biomass | mg mg–1 |
| Y5 | Hydrogen yield over lactate | mg mL–1 |
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©2016 by De Gruyter
Artikel in diesem Heft
- Frontmatter
- Preface to the Special Issue dedicated to the First International Energy Conference, IEC 2015
- Derivation of an Upscaled Model for Mass Transfer and Reaction for Non-Food Starch Conversion to Bioethanol
- Elucidating Kinetic, Adsorption and Partitioning Phenomena from a Single Well Tracer Method: Laboratory and Bench Scale Studies
- Thermodynamic Analysis of Ethanol Synthesis from Glycerol by Two-Step Reactor Sequence
- Modeling the Transient VOC (toluene) Oxidation in a Packed-Bed Catalytic Reactor
- Substrate Feeding Strategy Integrated with a Biomass Bayesian Estimator for a Biotechnological Process
- Comparison Tools for Parametric Identification of Kinetic Model for Ethanol Production using Evolutionary Optimization Approach
- Hydrodeoxygenation of Phenol Over Sulfided CoMo Catalysts Supported on a Mixed Al2O3-TiO2 Oxide
- Experimental and Computational Analysis of Single Phase Flow Coiled Flow Inverter Focusing on Number of Transfer Units and Effectiveness
- Dynamic Effectiveness Factor for Catalytic Particles with Anomalous Diffusion
- Experimental and Artificial Neural Network Modeling of a Upflow Anaerobic Contactor (UAC) for Biogas Production from Vinasse
- Novel Feedback Control to Improve Biohydrogen Production by Desulfovibrio alaskensis
- Influence of an Alkaline Zeolite on the Carbon Flow in Anaerobiosis of Three Strains of Saccharomyces cerevisiae
- CCS, A Needed Technology for the Mexican Electrical Sector: Sustainability and Local Industry Participation
- Olefins and Ethanol from Polyolefins: Analysis of Potential Chemical Recycling of Poly(ethylene) Mexican Case
- CFD Simulations of Copper-Ceria Based Microreactor for COPROX
Artikel in diesem Heft
- Frontmatter
- Preface to the Special Issue dedicated to the First International Energy Conference, IEC 2015
- Derivation of an Upscaled Model for Mass Transfer and Reaction for Non-Food Starch Conversion to Bioethanol
- Elucidating Kinetic, Adsorption and Partitioning Phenomena from a Single Well Tracer Method: Laboratory and Bench Scale Studies
- Thermodynamic Analysis of Ethanol Synthesis from Glycerol by Two-Step Reactor Sequence
- Modeling the Transient VOC (toluene) Oxidation in a Packed-Bed Catalytic Reactor
- Substrate Feeding Strategy Integrated with a Biomass Bayesian Estimator for a Biotechnological Process
- Comparison Tools for Parametric Identification of Kinetic Model for Ethanol Production using Evolutionary Optimization Approach
- Hydrodeoxygenation of Phenol Over Sulfided CoMo Catalysts Supported on a Mixed Al2O3-TiO2 Oxide
- Experimental and Computational Analysis of Single Phase Flow Coiled Flow Inverter Focusing on Number of Transfer Units and Effectiveness
- Dynamic Effectiveness Factor for Catalytic Particles with Anomalous Diffusion
- Experimental and Artificial Neural Network Modeling of a Upflow Anaerobic Contactor (UAC) for Biogas Production from Vinasse
- Novel Feedback Control to Improve Biohydrogen Production by Desulfovibrio alaskensis
- Influence of an Alkaline Zeolite on the Carbon Flow in Anaerobiosis of Three Strains of Saccharomyces cerevisiae
- CCS, A Needed Technology for the Mexican Electrical Sector: Sustainability and Local Industry Participation
- Olefins and Ethanol from Polyolefins: Analysis of Potential Chemical Recycling of Poly(ethylene) Mexican Case
- CFD Simulations of Copper-Ceria Based Microreactor for COPROX