Applications générales
R2026bSimulink® permet de modéliser et simuler un large éventail de systèmes dynamiques. Ces exemples de modèles illustrent diverses applications générales, de la plus simple à la plus complexe.
Sélection d՚exemples
Simulation of Bouncing Ball
Uses two models of a bouncing ball to show different approaches to modeling hybrid dynamic systems with Zeno behavior. Zeno behavior is informally characterized by an infinite number of events occurring in a finite time interval for certain hybrid systems. As the ball loses energy, the ball collides with the ground in successively smaller intervals of time.
Analyze Impact of Model Parameters on Bouncing Ball Simulation
Analyzes the impact of the damping coefficient on a mass-spring-damper model of the dynamics of a bouncing ball. The example runs a set of simulations. Each simulation uses a different value of the parameter that represents the damping coefficient. By visualizing and postprocessing the results of the simulations, the example explores these questions:
Single Hydraulic Cylinder Simulation
Use Simulink® to model a hydraulic cylinder. You can apply these concepts to applications where you need to model hydraulic behavior.
Modèle thermique d'une maison
Cet exemple montre comment utiliser Simulink® pour créer le modèle thermique d’une maison. Ce système modélise l’environnement extérieur, les caractéristiques thermiques et le système de chauffage de la maison.
Temperature Measurement System Using Nonlinear Behavioral Data of Type S Thermocouple
Build and simulate a temperature measurement system that uses a nonlinear dataset describing the behavior of a type S thermocouple.
Digital Waveform Generation: Approximate a Sine Wave
Design and evaluate a sine wave data table for use in digital waveform synthesis applications in embedded systems and arbitrary waveform generation instruments.
Détection précise des passages par zéro
Cet exemple montre comment fonctionne la détection des passages par zéro dans Simulink®. Simulink utilise la détection des passages par zéro pour simuler précisément un changement de modèle abrupt ou une discontinuité sans réduire les pas de temps du solveur. Pour plus d’informations, consultez Zero-Crossing Detection.
Spiral Galaxy Formation Simulation Using MATLAB Function Blocks
Use MATLAB Function blocks to simulate and plot galaxy interactions.
Counters Using Conditionally Executed Subsystems
Implement counters using Enabled and Triggered subsystems. In this example, the model sldemo_counters controls flow of water into a tank and uses a counter to count the number of times overflow occurs, where overflow occurs when the water level in the tank is 8 meters or more for 30 seconds or more.
Model Stick-Slip Friction and Hard Stops in Mass-Spring-Damper System
One way you can incorporate hard stops and friction changes from stick-slip motion into a mass-spring-damper model.
Contrôle bang-bang (TOR ou Tout ou Rien) en utilisant une logique temporelle
Cet exemple montre comment utiliser Stateflow® pour modéliser un système de contrôle de température bang-bang (TOR) pour une chaudière. La dynamique de la chaudière est modélisée dans Simulink®.
Pendule inversé avec animation
Cet exemple montre comment utiliser Simulink® pour modéliser et animer un système de pendule inversé. Un pendule inversé a son centre de masse au-dessus de son point de pivot. Pour maintenir la stabilité de cette position, le système implémente une logique de contrôle pour déplacer le point de pivot au-dessous du centre de masse quand le pendule commence à tomber. Le pendule inversé est un problème de dynamique classique utilisé pour tester les stratégies de contrôle.
Système à double masse-ressort
Cet exemple montre comment modéliser un système à double masse-ressort avec une fonction de forçage qui varie périodiquement. Le modèle utilise des blocs State-Space pour représenter le système physique et l’estimateur ainsi qu’un bloc Level-2 MATLAB S-Function pour animer le système à masse pendant la simulation. Le capteur et l’actionneur sont reliés à la masse de gauche. Cet exemple utilise l’estimation des états et le contrôle du régulateur linéaire-quadratique (LQR).
Tank Fill and Empty with Animation
Model the dynamics of liquid in a tank. The model simulates liquid inflow and outflow and displays an animated visualization of the process.
Simulating Systems with Variable Transport Delay Phenomena
Two cases where you can use Simulink® to model variable transport delay phenomena.
Foucault Pendulum Model
Model a Foucault pendulum. The Foucault pendulum was the brainchild of the French physicist Leon Foucault. It was intended to prove that Earth rotates around its axis. The oscillation plane of a Foucault pendulum rotates throughout the day as a result of the axial rotation of the Earth. The plane of oscillation completes a whole circle in a time interval T, which depends on the geographical latitude.
Foucault Pendulum Model with Simulink 3D Animation
Animate the Foucault Pendulum Model in the Simulink® 3D Animation™ environment. You can modify the pendulum location by changing the Latitude constant values in the model and other parameters in MATLAB® workspace.
Explore Variable-Step Solvers with Stiff Model
The behavior of variable-step solvers in a Foucault pendulum model. Simulink® solvers ode45, ode15s, ode23, and ode23t are used as test cases. Stiff differential equations are used to solve this problem. There is no exact definition of stiffness for equations. Some numerical methods are unstable when used to solve stiff equations and very small step sizes are required to obtain a numerically stable solution to a stiff problem. A stiff problem may have a fast changing component and a slow changing component.
Exploring the Solver Jacobian Structure of a Model
The example shows how to use Simulink® to explore the solver Jacobian sparsity pattern, and the connection between the solver Jacobian sparsity pattern and the dependency between components of a physical system. A Simulink model that models the synchronization of three metronomes placed on a free moving base are used.
Use Adaptive Zero-Crossing Location for More Robust Simulations
How the adaptive algorithm for zero-crossing location can improve simulation speed and robustness for systems that exhibit Zeno behavior, such as chattering.
Four Hydraulic Cylinder Simulation
Use Simulink to create a model with four hydraulic cylinders. The model has a single pump and four actuators.
Two Cylinder Model with Load Constraints
Use Simulink to model a rigid rod supporting a large mass interconnecting two hydraulic actuators. This model eliminates the springs as it applies the piston forces directly to the load.
Model Conveyor Belt as Cyber-Physical System
Model a variable-speed conveyor belt as a cyber-physical system by combining continuous-time, discrete-event, and finite-state modeling techniques. The model in this example integrates the modeling techniques required to represent the cyber-physical system into a single simulation environment by using Simulink®, SimEvents®, and Stateflow®.
Power Analysis of Spring-Mass-Damper System
Analyze mechanical power of mass-spring damper system.
Van der Pol Oscillator
Model the second-order Van der Pol (VDP) differential equation in Simulink®. In dynamics, the VDP oscillator is non-conservative and has nonlinear damping. At high amplitudes, the oscillator dissipates energy. At low amplitudes, the oscillator generates energy. The oscillator is given by this second-order differential equation:
Collision Avoidance and Trajectory Tracking of an Autonomous Surface Vessel
Follow a pre-defined trajectory and avoid collisions.
