Introduction to Model-Based Systems Design

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Course Description

Introduction to model-based system design: Model-in-the-Loop (MIL), Software-in-The-Loop Simulations (SIL), Hardware-in-the-Loop (HIL), Real-Time Simulations, Targeting, Verification and Validation, Design of Experiments, Model Refinement.

Course Objectives

After successfully completing this course the student should be able to:

  1. Build mathematical models for components in a system.
  2. Follow a process of continuous refinement and improvement to generate accurate models.
  3. Connect component models together to model a larger more complex system.
  4. Setup and run Model-in-the-Loop Simulations (MIL).
  5. Setup and run real-time simulations for a physical system.
  6. Setup and run Hardware-in-the-Loop Simulations (HIL).
  7. Apply basic control algorithms to a real physical system.
  8. Deploy a control algorithm on a real-time target.
  9. Apply verification and validation methods to a model of a physical systems.
  10. Use Design of Experiment methods to create models of physical systems.

Course Outline

  1. Model-Based Design fora small system
    1. Motor Model
    2. Generator Model
    3. Controller Model
    4. SimDriveline Intro
  2. Simulink Simulations
    1. Explore the system response using different control methods.
    2. Tune the system
    3. Explore system limitations
    4. Understand and refine motor models.
  3. Real-time simulations with xPC
    1. Plant and Controller Implement on Single Target
  4. Implement controller on MPC566 or MPC5554 target
    1. Install hardware and software.
    2. Use Freescale RAppID Toolboxor MathWorks 555 Toolbox
    3. Wire up system to familiarize students with pin outs
    4. Explore analog inputs,digital and PWM outputs
  5. Processor In The Loop Real-Time Simulations
    1. Controller on Freescale Target
    2. Plant on Real-Time Target
    3. Display Performance on Virtual Gauge Display
    4. Data Collection of Performance
  6. Test controller on real system
    1. Observe system performance
    2. Observe the effect of different control methods.
    3. Tune the system
  7. Model Verification
    1. Data Collection of Physical Model Response
    2. Comparison of Physical Plant Response to Model Response
  8. Design of Experiments to Collect Experimental Data on Motor and Generator
    1. Automatically Generate Test Schedule to Obtain Data
    2. Run Experiments and Collect Data
    3. Generate Models for Components
      1. Table-Lookup
      2. Curve Fits
  9. Model Refinement and Re-Verification
    1. Update Models to Include Measured Data
    2. Comparison of Updated Physical Plant to Model
  10. Further Exploration of Alternate Control Methods as Time Permits


Course Notes

Freescale MPC555x Documentation

Visit Model-Based Design Courses at The MathWorks Website

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