Model-Based Design with MATLAB and SIMULINK Masterclass

Course Highlights

This five-day course is designed for those who want to adopt Model-Based Design for control or embedded applications in their workflow environement using MATLAB and SIMULINK. The coures is intended for beginning users and those looking for a review. No prior programming experience or knowledge of MATLAB and SIMULINK are assumed. Themes of MATLAB basic programming, SIMULINK for system and algorithm modeling are explored throughout the course. Topic include:

  • Basic MATLAB programming
  • SIMULINK for system and algorithm modeling
  • Identifying the main elements in Model-Based design
  • Modeling and simulating physical systems and algorithms
  • Automatically generating code from SIMULINK
  • Continuously verifying and validating throughout the development cycle

Course Objectives

The aim of the course is to provide basic knowledge and proper techniques of MATLAB programmin and SIMULINK system and algorithm modeling for model-based design implementation in the area of control and embedded applications.

Who Must Attend 

This hands-on course is designed for beginner users. It is especially useful for those who want to gain a fundamental understanding of MATLAB and SIMULINK to adopt model-based design workflow. Engineers, researchers, scientists, and managers working with systems level design will be shown an easy-to-use approach in using MATLAB and SIMULINK.

Course Benefits

Upon the completion of the course, the participants will be able to identify the main elements in Model-Based Design, using SIMULINK as a graphical representation of a system and its components, automatically generate code from SIMULINK model and continuosly verifying and validating throughout the development cycle. 

Prerequisites

No prior knowledge of MATLAB and SIMULINK is required. Familiarity with undergraduate level mathematics and experience with basic computer operations is recommended.

Course Outline 
Day 1 of 5

Working with MATLAB User Interface

Objective: Become familiar with the main features of the MATLAB integrated design environment and its users interfaces. Get an overview of courses themes. 

  • Reading data from files
  • Saving and loading variables
  • Plotting data
  • Customizing plots
  • Exporting graphics for use in other applications


Variables and Commands

Objective: Enter MATLAB® commands with emphasis on creating variables, accessing and manipulating data in vector variables, and creating basic visualizations. Collect MATLAB commands into scripts for ease of reproduction and experimentations.

  • Entering commands
  • Creating numeric and character variables
  • Making and annotating plots
  • Getting Help
  • Creating and running script files

Analysis and Visualization with Vectors

Objective: Perform mathematical and statistical calculations with vectors and creating basics visualizations. Use MATLAB® syntax is to perform calculations on whole data sets with single command. 

  • Performing calculations with vectors
  • Accesing and modifying values in vectors
  • Creating multiple plots
  • Commenting and publishing scripts


Day 2 of 5

Conditional Data Selection

Objective: extract and analyze subsets of data that satisfy give criteria.

  • Logic operatins and variables
  • Finding and counting
  • Logical indexing

 
Flow Control

Objective: Create flexible code that can interact with the user, make decision and adapt to different situation.

  • Programming constructs
  • User Interaction
  • Flow control
  • Loops

 
Writing Functions

Objective:increase automation by encapsulating modular tasks as user-defined functions. Understanding how  MATLAB® resolves references to files and variable. Use MATLAB development tools to find and correct problems with code.

  • Creating functions
  • Calling functions
  • Setting the MATLAB pah
  • Debugging MATLAB Editor
  • Using breakpoints
  • Creating and usin structures


Day 3 of 5

Creating and Simulating a Model 

ObjectiveCreate a simple Simulink model, simulate it, and analyze the results.

  • Introduction to the SIMULINK interface
  • Potentiometer system
  • System inputs and outputs
  • Simulation and analysis


Modeling Programming Constructs 

Objective: Model and simulate basic programming constructs in Simulink.

  • Comparisons and decision statements
  • Zero crossings
  • MATLAB Function block


Modeling Discrete Systems 

ObjectiveModel and simulate discrete systems in Simulink.

  • Discrete signals and states
  • PI controller system
  • Discrete transfer functions and state space systems
  • Multirate discrete systems


Modeling Continuous Systems 

ObjectiveModel and simulate continuous systems in Simulink.

  • Continuous states
  • Throtthe system
  • Continuous transfer functions and state space systems
  • Physical boundaries

Day 4 of 5

Solver Selection

ObjectiveSelect a solver that is appropriate for a given SIMULINK model.

  • Solver behavior
  • System dynamics
  • Discontinuities
  • Algebraic loops

Developing Model Hierarchy 

ObjectiveUse subsystems to combine smaller systems into larger systems.

  • Subsystems
  • Bus signals
  • Masks


Modeling Conditionally Executed Algorithms 


ObjectiveCreate subsystems that are executed based on a control signal input. 

  • Conditionally executed subsystem
  • Enabled subsystems
  • Triggered subsystems
  • Input validation model


Creating Libraries 


ObjectiveUse libraries to create and distribute custom blocks.

  • Create and populate libraries
  • Manage library links
  • Add a library to the SIMULINK library browser

Day 5 of 5

Introduction to Model-Based Design

ObjectiveGet a brief overview of the elements that comprise Model-Based design.

Modeling

ObjectiveConnect design specifications, such as requrements and interfaces, to a projec containing SIMULINK models and other supporting files.

  • SIMULINK models as system diagrams
  • Model management
  • Requirements traceability
  • Configuration management
  • Modeling standards
  • Model documentation


Simulation and Analysis

ObjectiveExplore ways to model physical systems and algorithm, optimize their designs and verify their behaviour and correctness. 

  • Plant modeling approach
  • Algorithm modeling apporaches
  • Control design and optimizatio
  • Model verification
  • Simulation performance


Implementation


ObjectiveGenerate standalone code from SIMULINK model. Inspect, test, and integrate the automatically generated code with external hand-written code.

  • Code generation from SIMULINK models
  • Code customization and inspections
  • Integration with external code
  • Code verification

Transitioning to Model-Based Design

ObjectiveDiscuss factors that can influence your adoption strategy to minimize risk and maximize return on investment.

  • Difference between traditional designa and Model-Based Design
  • Supporting competencies in Model-Based design
  • Best practices for Model-Based Design
  • Involving Mathworks in your transition

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