Applying Control Design with MATLAB and SIMULINK

Course Highlights

Comprehensive control design case studies demonstrate effective techniques for improving efficiency in the use of MATLAB and SIMULINK for modeling and simulation. The course includes hands-on exercises with the Control System Toolbox and SIMULINK Control Design, and shows how to linearize a model and develop control laws using a variety of design methodologies.
Topics include:

• Control System Design Overview
• System Modeling
• System Analysis
• Control Design
• Controller Implementation

Course Objectives

The aim of the course is to provide general knowledge for participants to use MATLAB and SIMULINK control system design tools to accelerate the design process for closed-loop control system.

Who Must Attend

Engineer, researchers, scientists, and managers who are involved in control engineering design and problem solving. It is also strongly recommended for those who would like to establish and strengthen their foundation in Control Engineering.

Course Benefits

Upon the completion of the course, the participants will gain a comprehensive understanding on utilizing the Control System Toolbox and SIMULINK Control Design to design and develop control system using a variety of design methodologies.

Prerequisites

Attended "Comprehensive MATLAB" and "Comprehensive SIMULINK" or equivalent experience using MATLAB and SIMULINK, and an understanding of terminology and concepts related to common control systems.

Course Outline

Day 1

Control System Design Overview
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
  1. Control design workflow
  2. Linearizing a model
  3. Finding system characteristics
  4. Setting controller requirements
  5. Tuning a controller
  6. Testing the controller

System Modeling
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

System Analysis
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
  1. Using the LTI Viewer
  2. Additional linearization examples

Day 2

Control Design
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

Controller Implementation
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