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In this paper, a nonlinear observer design is presented for simultaneous parameter estimation and state variables estimation. The case of study is microalgae cultures for biodiesel generation, where reaction rates, biomass concentration, intracellular quota and nitrogen concentration are critical variables that provide information about the state of the process. However, these variables might be difficult to measure due to the lack of specific instruments, high sensor costs or infeasibility of installation in the process. Therefore, two observer-based virtual sensors are presented in this paper as an analytical alternative to perform estimation of the main important variables or parameters of the process: a nonlinear adaptive observer and a nonlinear high-gain observer. The observers are based on the Droop´s mathematical model that describes the ability of microalgae to store nutrients and the decoupling between substrate uptake and biomass growth. Numerical simulations are made in order to evaluate the performance of the proposed observers.

This paper presents the design of a maximum power point-tracking (MPPT) technique for DC–DC converters that are used in energy-harvesting systems based on thermoelectric generators. This technique is based on the analysis of the characteristics of the converter to measure the open-circuit voltage indirectly. The main contribution of this article is that the algorithm measures the voltage at the maximum power point without the need to disconnect the source of the circuit, as happens when the fractional open-circuit voltage (FOCV) technique is used. The algorithm is based on a predetermined initial duty cycle, which is applied to the circuit, and the input voltage and input current are read. With these values, the open-circuit voltage and short-circuit current are calculated with equations obtained from the circuit. Then, it calculates the duty cycle at the maximum power point and applies it to the circuit. If this duty cycle does not obtain the maximum power from the circuit, the algorithm starts a second stage based on fuzzy logic to calculate an increase or decrease in the duty cycle. The designed technique was evaluated using a topology based on a DC–DC flyback converter variant and was compared with the P&O technique and obtained better results. The designed technique provides between 3.9% and 5.6% more power to the load than the P&O technique in a 20 W system.

Microalgal biomass has the capacity to accumulate relatively large quantities of triacylglycerides (TAG) for the conversion of methyl esters of fatty acids (FAME) which has made microalgae a desirable alternative for the production of biofuels. In the present work Verrucodesmus verrucosus was evaluated under autotrophic growth conditions as a suitable source of oil for biodiesel production. For this purpose BG11 media were evaluated in three different light:dark photoperiods (L:D, 16:08, 12:12, 24:0) and light intensities (1000, 2000 and 3000 Lux) in a photobioreactor with a capacity of three liters, the evaluation of the microalgal biomass was carried out through the cell count with the use of the Neubauer chamber followed by the evaluation of the kinetic growth parameters. So, the lipid accumulation was determined through the lipid extraction with a Soxhlet system. Finally, the fatty acid profile of the total pooled lipids was determined using gas chromatography-mass spectroscopy (GC-MS). The results demonstrate that the best conditions are a photoperiod of 12 light hours and 12 dark hours with BG11 medium in a 3 L tubular photobioreactor with 0.3% CO2, 25 °C and 2000 Lux, allowing a lipid accumulation of 50.42%. Palmitic acid is identified as the most abundant fatty acid at 44.90%.

International audience; This work presents the modeling and simulation of a hydraulic network with four nodes and two branches that form a two-level water distribution system. It also proposes a distribution of hydraulic valves that allows emulating a leak using a valve and different network configurations, e.g., simple ducts, closed networks and branched networks. The network is modeled in the steady state considering turbulent flow. Numerical experiments are performed, and the results show that the proposed network is useful for the design of leakage diagnosis and control algorithms in different configurations and leakage scenarios

Fossil fuel combustion produces around 98% of coal emissions. Therefore, liquid and gaseous biofuels have become more attractive due to their environmental benefits. The biodiesel production process requires measurements that help to control and supervise the variables involved in the process. The measurements provide valuable information about the operation conditions and give estimations about the critical variables of the process. The information from measurements is essential for monitoring the state of a process and verifying if it has an optimal performance. The objective of this study was the conception of a virtual sensor based on the Extended Kalman Filter (EKF) and the model of a batch biodiesel reactor for estimating concentrations of triglycerides (TG), diglycerides (DG), monoglycerides (MG), methyl ester (E), alcohol (A), and glycerol (GL) in real-time through measurement of the temperature and pH. Estimation of the TG, DG, MG, E, A, and Gl through this method eliminates the need for additional sensors and allows the use of different types of control. For the performance analysis of the virtual sensor, the data obtained from the EKF are compared with experimental data reported in the literature, with the mean square error of the estimate then being calculated. In addition, the results of this approach can be implemented in a real system, since it only uses measurements available in a reactor such as temperature and pH.

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