A DC motor velocity control in feedback systems usually requires a velocity sensor, which increases the controller cost. Additionally, the velocity sensor used in industrial applications presents several disadvantages such as maintenance requirements and signal conditioning. In this work, we propose a robust velocity control scheme applied to a DC motor based on estimation strategies using a sliding-mode observer. This means that measurements with mechanical sensors are not required in the controller design. The proposed observer estimates the rotational velocity and load torque of the motor. The controller design applies the exact-linearization technique combined with the super-twisting algorithm to achieve robust performance in the closed-loop system. The controller validation was carried out by experimental tests using a workbench, which is composed of a control and data acquisition Digital Signal Proccessor board, a DC-DC electronic converter, an interface board for signals conditioning, and a DC electric generator connected to an adjustable resistive load. The simulation and experimental results show a significant performance of the proposed control scheme. During tests, the accuracy, robustness, and speed response on the controller were evaluated and the experimental results were compared with a classic proportional-integral controller, which uses a conventional encoder.

In this article, we present a system to measure current in the range of 0 to 10 $\mathsf{\mu }$A with high-voltage isolation up to 5 kV. This current monitor consists of three ammeters connected in series, to improve the resolution in the measurement. The design features several innovative elements such as using low voltage to provide power to the devices to measure the current and digitize it with a sampling frequency of 1 KHz, it is generated based on a DC-DC converter that produces three voltages, +12 V, −12 V, and 5 V, from a conventional 10 V source. The three voltages are referenced to the same floating ground. The DC-DC converter has a high voltage insulation up to 5 kV and four optocouplers with an insulation up to 20 kV are used to read the digitized data. The introduction of a DC-DC converter contributed to reduce the noise level in the analog part of the circuit which has been resolved implementing shields inside the board. In particle physics, several systems are used to detect particles in high-energy physics experiments such as Gas Electron Multiplier (GEM), micromegas, etc. GEMs suffer small deteriorations due to discharges in constant operation and require monitoring the current consumption at high frequency (1 kHz). In this work, we present the design and operation of a 0 to 10 $\mathsf{\mu }$A auto scale ammeter. The results obtained by monitoring the current in a 10 × 10 cm${}^2$ GEM are shown.

Image segmentation is a critical step in computer vision systems for phytosanitary diagnosis in cacao production. However, the reliability of classical segmentation methods remains insufficiently assessed under real field conditions, where images captured under non-standardized conditions are often affected by variable illumination, complex backgrounds, partial occlusions, and chromatic similarity between cacao pods and surrounding vegetation. This study compares global thresholding, K-means clustering, and GrabCut using 343 cocoa pod images captured in uncontrolled agricultural environments with non-standardized mobile devices; low-resolution images were retained to preserve external validity. Robustness was assessed on the full dataset using unsupervised structural metrics, including the segmented area ratio (AS), the largest component ratio (LCR), and the catastrophic failure rate (FC), while accuracy was validated on 50 manually annotated images using Intersection over Union (IoU). Wilcoxon signed-rank tests indicated statistically significant differences among methods. GrabCut achieved the best performance (IoU = 0.814), high structural coherence (LCR = 0.985), and a low catastrophic failure rate (FC = 1.7%). In contrast, K-means showed severe fragmentation and instability, whereas global thresholding was highly sensitive to illumination variability and complex backgrounds. These results indicate that GrabCut provides a robust training-free baseline for cocoa pod segmentation under uncontrolled field conditions, particularly for offline phytosanitary analysis where annotated datasets, supervised training, or GPU-based deployment are limited.

High-accuracy mechatronic systems require a control algorithm to realize trajectories or positions. On the other hand, the acquisition of data and embedded system design configurable is a very important part to guarantees processing in hardware, high performance, reception, and send of data that generally is defined by the applications to which it is intended. Therefore, the increasing demands in the improvement of the accuracy systems based on modern programable devices are being applied in the scientific and engineering areas. This paper presents a novel mechatronic approach to experimental validation of a feed drive system with ball screw. The description of an original FPGA-based configurable design is introduced which consists of an own design approaches of hardware architecture. Finally, based on a built prototype of a feed drive system with ball screw, the PID controller implemented and the mathematical model, in both cases, were applied in order to establish the comparison between the responses, seeking to observe if the experimental results show a great difference with respect to the simulation data. A cost-effective solution using a single chip low-cost FPGA for feed-drive system is presented to the closed-loop control present approximately the same response as that of the system model used in the simulation. Experimental results demonstrate an excellent positioning control and processing performance of the data configured on the FPGA Firmware, which validates the feasibility and effectiveness of the proposal.

Partiendo de la teoría de masa efectiva y el modelo de Thomas-Fermi (TF) se ha establecidoel perfil de potencial para un sistema tipo delta-dopado simple en Arseniuro de Galio(GaAs) tipo n. Resolviendo la ecuación de Schrödinger asociada al sistema, se han calculadolos autovalores y las autofunciones del perfil de potencial, determinando así su estructura electrónica.Con ayuda de la teoría de Matriz Densidad se ha determinado el cambio en el índicede refracción (CIR) lineal y no lineal del sistema. De tal manera que, añadiendo un término dedesorden en el sistema (ζ), es posible calcular numéricamente los cambios en la estructura electrónicay las propiedades ópticas no lineales. Se ha determinado que con valores de ζ alrededordel 10% asociado a la densidad de impurezas (N2D), el cambio en el índice de refracción linealy no lineal no sufre cambios significativos. Por otro lado, cuando se incrementa el desorden enla densidad de impurezas introducidas en el material semiconductor, el comportamiento de lapropiedad óptica se pierde por completo. Finalmente, notamos que al introducir desorden enla intensidad del laser, la propiedad óptica no sufre cambios. El presente estudio teórico podríapredecir el efecto del desorden estructural sobre el comportamiento del CIR en los dispositivosbasados en delta dopados al momento de su síntesis.