Biological control is the artificial manipulation of natural enemies of a pest for its regulation to densities below a threshold for economic damage. The authors address the biological control of a class of pest population models using a modelbased robust feedback approach. The proposed control framework is based on a recursive cascade control scheme exploiting the chained form of pest population models and the use of virtual inputs. The robust feedback is formulated considering the nonlinear model uncertainties via a simple and intuitive control design. Numerical results on three pest biological control problems show that the proposed model-based robust feedback can regulate the pest population at the desired reference via the manipulation of a biological control action despite model uncertainties.

The hydrodynamic of modified up-flow anaerobic sludge blanket (UASB) treating organic fraction of municipal solids wastes (OFMSW) was investigated using tracer test experiments and residence time distribution (RTD) based models. The modified UASB digester employing the up-flow reactor concept was composed of the sludge bed, localized at the bottom of the reactor, a buffer zone above the sludge bed, a section with the OFMSW, and an upper section with a solid–liquid–gas separator. The solid-state section with the OFMSW allows the separation of hydrolytic and methanogenic phases, reducing the acidification of the reactor. The hydraulic flow transports the faster biodegradable fraction from the packing section to the sludge bed, favoring the methane productivity. Residence time distribution curves were analyzed by three tracer test models (axial dispersion model ADM, tanks in series model TIS and a multiple parameter model MPM). The MPM was successfully fitted to the experimental data.

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Microalgae are used to produce renewable biofuels (biodiesel, bioethanol, biogas, and biohydrogen) and high-value-added products, as well as in bioremediation and CO2 sequestration tasks. In the case of anaerobic digestion of microalgae, biogas can be produced from mainly proteins and carbohydrates. Anaerobic digestion is a complex process that involves several stages and is susceptible to operational instability due to various factors. Robust controllers with simple structure and design are necessary for practical implementation purposes and to achieve a proper process operation despite process variabilities, uncertainties, and complex interactions. This paper presents the application of a control design based on the modeling error compensation technique for the anaerobic digestion of microalgae. The control design departs from a low-order input–output model by enhancement with uncertainty estimation. The results show that achieving desired organic pollution levels and methanogenic biomass concentrations as well as minimizing the effect of external perturbations on a benchmark case study of the anaerobic digestion of microalgae is possible with the proposed control design.