Examinando por Materia "Simulink"

Mostrando 1 - 4 de 4
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    Ítem
    Avionics system for a mini-helicopter robot in a rapid software prototyping environment
    (2010-01-01) Vélez S., C.M.; Hernández L., M.; Agudelo T., A.; Vélez S., C.M.; Hernández L., M.; Agudelo T., A.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    This paper describes the hardware and software of the avionics for a mini-helicopter robot called Colibrí, which provides the instrumentation, intelligence, and energy to the autonomous navigation. The paper describes the function of each electronic device in the navigation system and explains the tools for rapid software prototyping. This programming environment uses a high-level graphical language like Simulink® to design a test model, and from it automatically build the executable code in C, which runs in the QNX real-time operating system during each flight. Matlab® Real-Time Workshop is the tool that enables this efficient programming methodology. The tests in pilot assisted flights show that the environment makes easy the development of state estimators, finite state machines, controllers and other subsystems. © 2010 IEEE.
  • Miniatura
    Ítem
    Estimación de parámetros, análisis de sensibilidad y validación del modelo SIR aplicado a datos históricos del virus A(H1N1) en México.
    (Universidad EAFIT, 2021-04-13) Gómez Osorio, Hamilton; Isaza Cadavid, Santiago; Osorio Marulanda, Pablo A.; Universidad EAFIT, Escuela de Ciencias, Departamento de Ciencias Matemáticas
    Este trabajo busca analizar el comportamiento epidemiológico de una enfermedad transmisible como la influenza A(H1N1), a partir de un modelo SIR, aplicado a un grupo de personas diagnósticadas con la enfermedad en México en el año 2009. En este se realiza una respectiva estimación de parámetros poblacionales, como lo es la tasa de contagio y la tasa de recuperación, y un análisis de sensibilidad utilizando la herramienta Simulink de MATLAB.
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    Ítem
    Mathematical modelling and simulation of a rocket’s take-off trajectory
    (Universidad Eafit, 2021-04-08) Vidal Correa, Juan Pablo; Murillo Gonzalez, Alejandro; Botero Botero, Maria Alejandra; Universidad Eafit, School of Sciences, Department of Mathematical Sciences
    A rocket is a vehicle that launches into space or describes a suborbital flight. It’s subjected to the forces of weight, thrust, and the aerodynamic forces, lift and drag. The relative magnitude and direction of the forces determines the flight trajectory of the rocket. The objectives of this paper are to model the rocket’s take-off trajectory and understand the tradeoff when using the main engine in conjunction with the lateral thrusters. Also, to obtain a linear model that represents the altitude obtained by the rocket in the ascending phase and to examine system behavior through stability and sensitivity analysis. Rocket’s trajectory is obtained in four situations depends on the engine or thrusters that are in operation. Linearization methods were used to replace the model by a simpler function due to the possibility of use tools for studying linear systems to analyze the behavior of a nonlinear function near a given point and because a linear model is required for certain types of analysis such as stability analysis. Finally, sensitivity analysis of the parameters of the model is used to study how the uncertainty in the output of a mathematical model can be apportioned to different sources of uncertainty in its inputs
  • Miniatura
    Ítem
    Modeling, simulation, and control of the spacecraft attitude dynamics
    (Universidad EAFIT, 2021-03-26) Ocampo, Carlos; Universidad EAFIT, School of Sciences, Department of Mathematical Sciences
    Based on the three-dimensional dynamics of a rigid body and Newton’s laws, the simplified dynamics of a spacecraft is studied and described through the systematical representation, mathematical modeling and also by a block diagram representation, to finally simulates the spacecraft dynamics in the Matlab programming environment called Simulink. It is paramount to be able to identify and recognize the attitude (often represented with the Euler angles) and position variables like the degrees of freedom (DOF) of the system and also the linear behavior. All this to conclude up about the non-linear behavior presented by the accelerations, velocities, positions and Euler angles (attitude) when those mentioned are plotted against time. In addition to this, the linearized system is found in order to facilitate the control analysis and stability analysis, at using linear analysis tools of Simulink and concepts like controllability and observability, reaching the point of determining under the previous concepts to proceed with the control design phase. Lastly, an uncertainty and sensitivity analysis is realized, by means the Monte-Carlo and the Linear regression method (in Simulink too), to find the torque like critical model input, since it has the greatest effect on the response variables in the system; and thus finally, to implement the Linear Quadratic Regulator (LQR) controller, at using the lqr Matlab function