Training - Courses

Objectives:

• Obtain a quick overview of The MathWorks and MATLAB
• Discuss course set-up, materials, and logistics
• Provide a “big picture” view of the course ahead
  

Objectives: Provide an overview of the control system design process and introduce how The MathWorks tools fit into that process. The details of each step in the design process will be covered in later chapters.

• The digital motion control system
• Control design workflow
• Linearizing a model
• Finding system characteristics
• Setting controller requirements
• Tuning a controller
• Testing the controller

Objectives: Discuss the various techniques used to model a system; from creating models based on data to creating models from mathematical equations.

• Model representations
• Black box modeling
• First principles modeling
• Gray box modeling

Objectives: Outline the different analysis tools available for understanding system behavior. Linear models are useful for control design algorithms, so there is focus on using the LTI Viewer (a powerful tool for analyzing linear models) and linearizing Simulink models. Finding specific system characteristics (system resonances, transient response, etc.) is also covered.

• Linearizing a system
• Using the LTI Viewer
• Additional linearization examples

Objectives: Illustrate the process of designing a compensator for different systems. Focus is on classical control design using the visualization capabilities of the SISO Design Tool. Common control techniques are covered, such as PID and Lead/Lag controllers.

• PID control
• Lead/Lag control
• Parameter tuning in Simulink

Objectives: Discuss steps that might be needed to effectively implement a controller on a real system. Controller implementation is often performed on a microprocessor, so controller discretization is covered. Also covered are methods for testing the controller in more realistic simulations.

• Physical and practical limitations of controllers
• Discretizing a controller
• Creating more realistic simulations