Abstract
One of major challenge in bio-hydrogen production process by using MEC process is nonlinear and highly complex system. This is mainly due to the presence of microbial interactions and highly complex phenomena in the system. Its complexity makes MEC system difficult to operate and control under optimal conditions. Thus, precise control is required for the MEC reactor, so that the amount of current required to produce hydrogen gas can be controlled according to the composition of the substrate in the reactor. In this work, two schemes for controlling the current and voltage of MEC were evaluated. The controllers evaluated are PID and Inverse neural network (NN) controller. The comparative study has been carried out under optimal condition for the production of bio-hydrogen gas wherein the controller output is based on the correlation of optimal current and voltage to the MEC. Various simulation tests involving multiple set-point changes and disturbances rejection have been evaluated and the performances of both controllers are discussed. The neural network-based controller results in fast response time and less overshoots while the offset effects are minimal. In conclusion, the Inverse neural network (NN)-based controllers provide better control performance for the MEC system compared to the PID controller.
Highlights
Microbial electrolysis cells (MEC) used for wastewater treatment are a novel and promising renewable energy technology that can produce H2 while the treatment is being performed
Precise control is required for the MEC reactor, so that the amount of current required to produce hydrogen gas can be controlled according to the composition of the substrate in the reactor
The Inverse neural network (NN)-based controllers provide better control performance for the MEC system compared to the PID controller
Summary
Microbial electrolysis cells (MEC) used for wastewater treatment are a novel and promising renewable energy technology that can produce H2 while the treatment is being performed. One important and interesting phenomenon of the MEC model is a competition between anodophilic and methanogenic microorganisms to consume the substrate in the anode compartment [2, 3] Competition among these microbial populations has severe. An initial study of this system used a model involving competition among anodophilic, methanogenic acetoclastic and hydrogenotrophic methanogenic microorganisms in the biofilm as reported by Pinto et al [4]. A model was trained, tested and validated to predict the hydrogen production profile None of these studies in the literature involve neural network based controller for biohydrogen gas production in the MEC. Electrochemical process The MEC voltage can be calculated using the theoretical values of electrode potentials by subtracting the ohmic, activation, and concentration losses. The maximum reaction rate of the acetoclastic methanogenic microorganism The half-rate (Monod) constant of the anodophilic microorganism The half-rate (Monod) constant of the acetoclastic methanogenic microorganism Mediator half-rate constant Half-rate constant The dimensionless cathode efficiency
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