LaTeX templates and examples — Reports

Esta es una plantilla utilizada para la presentación de trabajos prácticos, cuenta con elementos predefinidos y distintas secciones. Originalmente fue diseñana para la cátedra de Simulación de Ingeniería en Sistemas pero se puede utilizar para cualquier otra cátedra

Plantilla para la entrega de informes de laboratorio en el programa de ingeniería mecatrónica de la Universidad Militar Nueva Granada.

En la actualidad, el estudio y análisis de los sistemas de control automático representan un campo de aplicación bastante extendido, esto debido a las imperantes necesidades por mejorar los procesos productivos, optimizar los recursos e incluso para predecir comportamientos, desde entornos educativos, investigativos o industriales, hasta entornos económicos, sociales y demás. En efecto, esto ha impulsado a los desarrolladores a buscar herramientas o alternativas que permitan aumentar las capacidades de cómputo al momento de desarrollar un sistema de control automático. Ahora bien, la instrumentación industrial desde hace muchos años viene comandada por los Autómatas Programables (PLC), dispositivos útiles e ideales para ejecutar las tareas de control de una planta, independientemente de la escala. El presente documento presenta el diseño e implementación de un controlador PID en una planta didáctica conformada con equipos industriales, haciendo uso de OPC y algunos conceptos de la teoría de control. Mediante la herramienta computacional MATLAB se realiza la identificación de la planta obteniendo su función de transferencia, y haciendo uso de algunas herramientas disponibles en este software, se determinan los parámetros de sintonía de un controlador tipo PID, para posteriormente sintonizar la estrategia de control implementada en un autómata programable de gama alta.

Projeto lab CE2

Baseado no Template MDPI/sensors

With the detectors currently off, LIGO has detected and gathered an abundance of data from the second observing run (O2). Some of which, captures the most recent triggers that are potential candidates for future gravitational waves, are analyzed more thoroughly. My responsibility as a student researcher is to perform independent checks on four of the most recent Compact Binary Coalescence (CBC) triggers. In order to do so, I compare the \(h(t)\) Omega scans of these events to the Gravity Spy classes. Omega scans are a detector characterization tool to help measure the Signal-to-Noise-Ratio (SNR) of transient noises during detections. This helps scientists distinguish the difference between a gravitational wave signal, which looks like a `chirp' versus a glitch in the data. Gravity Spy is a citizen science program that helps LIGO in classifying glitches to improve machine learning for gravitational wave signals. For each event I determine if it looks like one of the known categories of solved or unsolved glitches seen in the Advanced LIGO detectors? My results are then recorded in the O2 event detection checklist. Omega scans are a `burst-type' search pipeline that detect glitches efficiently. The Omega scan is labeled using time measured in seconds on the x-axis, frequency measured in Hz on the y-axis and the signal measured is normalized to demonstrate how `loud' the noise is.

The kernel is a computer program that has complete control over the operating system. It handles the input/output requests and translates them into data-processing instructions for the CPU. It handles not only the memory, but also peripherals. The kernel controls the tasks that are managed in the running system, some of these are running processes, hardware management and handling interrupts, in the kernel space. On the other hand, the user performs in the user space. This separation helps to prevent data interfering that can cause instability and slowness, or worse, malfunctioning application programs that can crash the entire operating system. The process scheduler decides which is the next task to run. In the following project we analyzed the behavior of the scheduler changing the default value of the runtime scheduling, this value is 950000µs for the scheduler real time running variable. According to this, 5% of the CPU time is reserved for processes that are not running under a realtime or deadline scheduling policy. On this project, this value specifies how much of the period time could be used by real-time and deadline scheduled processes on the system.

Template para o relatório de drawback.

Plantilla para informes de proyectos