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Experimental studies of two-phase anaerobic digestion of corn steep liquor (a waste product from processing corn grain for starch extraction) were performed. For the first time, an automatic mode of operation was implemented in continuous processes with simultaneous production of hydrogen and methane using the developed computer system for monitoring and control of pilot bioreactors. The best results for daily biogas yield were obtained at an organic load of 20 g/L for hydrogen producing bioreactor, as the daily yield of biohydrogen is 0.74 dm3/L at a hydrogen concentration in biogas of 32.6% (0.24 dm3/L pure biohydrogen) and the daily biomethane yield in the methane producing bioreactor is 0.587 dm3/L at a methane concentration in biogas of 69% (0.4 dm3/L pure biomethane). The obtained energy is more than 40% compared to the traditional single-stage methane production process. A disadvantage is the need for additional purification from hydrogen sulfide of both gases before obtaining electricity and/or heat.

This paper presents a new Composed Adaptive Controller (CAC) for trajectory tracking of a methane fermentation process in stirred tank bio-reactors. The referred biotechnological process is described by a second-order non-linear model based one-stage reaction scheme. The proposed controller comprises an Algebraic Differential Estimation (ADE) based compensation component and a Recursive Model Free Controller (RMFC) stabilization component which dose not require any knowledge of the physical model parameters. The proposed entire control enables trajectories tracking of a variable set point trajectory and over performs the existing anaerobic digestion control schemes, such as a classical Proportional-Integral-Derivative (PID) control or a nonlinear PI control. Computer simulation examples illustrate the performance and robustness of the proposed approach.

The paper deals with identifiability and observability of methane fermentation (MF) processes. In such kind of processes, generally carried out in continuously stirred tank bioreactors, the organic matter is depolluted by microorganisms into biogas and compost in the absence of oxygen. The biogas is an additional energy source, which can replace fossil fuel sources. The differential algebraic approach of general observation problems has been applied to investigate the identification and observation of a simple MF model. The major discovery is that the biomass specific growth rate can be stably estimated from easily measured quantities: the dilution rate and the biogas flow rate. Next if the yield coefficients are assumed known then, of course, the biomass concentration is observable. Unfortunately, even under the latter strongest assumption the substrate concentration is not observable. This concentration becomes observable if an additional model, say the Monod model, is assumed for the specific growth rate. Illustrative simulations are presented. The experimental validation is under investigation.

In the paper some problems of the mathematical modeling of anaerobic (methane) fermentation of animal waste in stirred tank bioreactors are considered. Laboratory experiments are carried out with highly concentrated organic pollutants and transient step responses of the control output for continuous methane fermentation are obtained. The dynamic behavior of this process is described by sets of deterministic nonlinear differential equations from 2nd order with different structures. Static characteristics are obtained with these models analytically. Investigations by computer simulation of the methane fermentation are performed with the aim to chose appropriate models for automatic control system design of this process.