Training - Courses

SL01: Simulink for System and Algorithm Modeling

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

This course targets engineers who are new to system and algorithm modeling and design validation in the Simulink environment. It applies basic modeling techniques and tools to developing Simulink block diagrams, including:

Modeling continuous-time, single- and multirate discrete-time, and hybrid systems
Understanding model hierarchy
Executing a condition-based system
Automating model simulations
Developing custom blocks and libraries

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	Detailed course outline

Day 1 of 2
Introduction	Objective: Define the steps to model systems using Simulink Model based Design Types of Modeling MathWorks modeling tools System modeling with Simulink Modeling steps
Introduction to System Modeling	Objective: Describe the model-based design process and system modeling in Simulink. System modeling with Simulink Model-Based Design with Simulink Electronic Throttle Control model
Modeling Algebraic System	Objective: Use Simulink to model and simulate algebraic systems. Define the potentiometer system Introduce the Simulink interface Create a Simulink model of the potentiometer system Simulate the model and analyze results
Modeling Logical Systems	Objective: Use Simulink to model and simulate logical systems Define the logical system Create a Simulink model for the logical system Introduce zero crossings Simulate the model and analyze the results Model the system with Embedded MATLAB
Modeling Continuous Systems		Objective: Use Simulink to model and simulate continuous systems Define the throttle system Create a Simulink model for the throttle system Define continuous states Choose a continuous solver Simulate the model and analyze results

	Day 2 of 2

	Modeling Discrete Systems		Objective: Use Simulink to model and simulate discrete systems. Define the IP controller system Create a Simulink model for the IP controller Define discrete states Choose a discrete solver Model multirate discrete systems

	Modeling Systems with Subsystems		Objective: Use subsystems to combine smaller systems into larger systems and to model signal driven systems. Create and use subsystems Define model callbacks Contrast virtual and non-virtual subsystems Model conditionally executed subsystems

	Combining Models into Diagrams		Objective: Use model reference to combine models Model referencing and subsystems Setup a model reference Model reference simulation modes View signals in referenced models Store parameters in referenced models

	Creating Custom Blocks and Libraries		Objective: Use masks and libraries to create and distribute custom blocks. Masking blocks Create new libraries Create configurable subsystems Add libraries to the Library Browser Compare libraries and model references

Prerequisites

Knowledge of MATLAB basics.

Course Length - 2 days

Price - $1,100.00

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Training - Courses

SL01: Simulink for System and Algorithm Modeling

Prerequisites

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