Training - Courses

SLBE: Simulink for System and Algorithm Modeling

This two-day course is for engineers who are new to system and algorithm modeling and design validation in Simulink. It demonstrates how to apply basic modeling techniques and tools to develop Simulink block diagrams. Topics include:

Creating and modifying Simulink models and simulating system dynamics
Modeling continuous-time, discrete-time, and hybrid systems
Modifying solver settings for simulation accuracy and speed
Building hierarchy into a Simulink model
Creating reusable model components using subsystems, libraries, and model references

If your application is Signal Processing or Communications, please refer to our Simulink^® for Signal Processing course.

VIEW SCHEDULE and Register SHARE with Manager/Colleague

	Detailed course outline

Day 1 of 2
Creating and Simulating a Model	Objective: Create a simple Simulink model, simulate it, and analyze the results. Define the potentiometer system Explore the Simulink environment interface Create a Simulink model of the potentiometer system Simulate the model and analyze results
Modeling Programming Constructs	Objective: Model and simulate basic programming constructs in Simulink. Comparisons and decision statements Zero crossings MATLAB Function block
Modeling Discrete Systems	Objective: Model and simulate discrete systems in Simulink. Define discrete states Create a model of a PI controller Model discrete transfer functions and state space systems Model multirate discrete systems
Modeling Continuous Systems	Objective: Model and simulate continuous systems in Simulink. Create a model of a throttle system Define continuous states Run simulations and analyze results Model impact dynamics

Day 2 of 2
Solver Selection	Objective: Select a solver that is appropriate for a given Simulink model. Solver behavior System dynamics Discontinuities Algebraic loops
Developing Model Hierarchy	Objective: Use subsystems to combine smaller systems into larger systems. Subsystems Bus signals Masks
Modeling Conditionally Executed Algorithms	Objective: Create subsystems that are executed based on a control signal input. Enabled subsystems Triggered subsystems Input validation model
Combining Models into Diagrams	Objective: Use model referencing to combine models. Compare model referencing and subsystems Set up a model reference Use model reference simulation modes View signals in referenced models Store parameters in referenced models
Creating Libraries	Objective: Use libraries to create and distribute custom blocks. Create and populate libraries Manage library links Add a library to the Simulink Library Browser

Prerequisites

MATLAB^® Fundamentals

Course Length - 2 days