Control System Design with
MATLAB and Simulink

Learn how to design, analyze, and optimize closed-loop control systems using MATLAB and Simulink

Complimentary Services: Post training email support & 1-hr consultation session within 1 month after the course completion!

TechSource Systems Pte Ltd

Course
Highlights

This two-day course provides a general understanding of how to accelerate the design process for closed-loop control systems using MATLAB® and Simulink®. Topics include:

  • Control system design overview
  • System modeling
  • System analysis
  • Control design
  • Controller implementation
TechSource Systems Pte Ltd

Who Should
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.

TechSource Systems Pte Ltd

Course
Prerequisites

MATLAB Fundamentals and Simulink for System and Algorithm Modeling or equivalent experience using MATLAB and Simulink. Also, an understanding of terminology and concepts related to common control systems.

TechSource Systems Pte Ltd

Course
Benefits

Upon the completion of the course, the participants will gain a comprehensive understanding on the following:

  • Plant modeling
  • Closed loop control system analysis
  • Compensator design
  • Controller implementation

Partners

TechSource Systems Pte Ltd
TechSource Systems Pte Ltd

TechSource Systems is MathWorks Authorised Reseller and Training Partner

Upcoming Program

  • Please keep me posted on the next schedule
  • Please contact me to arrange customized/ in-house training

Course Outline

Control System Design Overview

Objective: Provide an overview of the control system design process and introduce how MATLAB and Simulink fit into that process. The details of each step in the design process are covered in later chapters.

  • Defining a control design workflow
  • Linearizing a model
  • Finding system characteristics
  • Setting controller requirements
  • Tuning controllers
  • Testing controllers
TechSource Systems Pte Ltd
TechSource Systems Pte Ltd

Model Representations

Objective: Discuss the various formats used for representing system models. Also highlights the pros and cons of each format.

  • Model representations overview
  • LTI objects
  • Simulink models

System Identification

Objective: Illustrate how to estimate system models based on measured data.

  • System identification overview
  • Data importing and preprocessing
  • Model estimation
  • Model validation
TechSource Systems Pte Ltd
TechSource Systems Pte Ltd

Parameter Estimation

Objective: Use measured data to estimate the values of a Simulink model’s parameters.

  • Parameter estimation overview
  • Model preparation
  • Estimation process
  • Parameter estimation tips

System Analysis

Objective: Outline the different analysis tools and functions available for understanding system behavior – such as system resonances, transient response, etc.

  • System analysis functions
  • Linear System Analyzer
  • DC motor analysis
  • Automation of analysis tasks
  • Open loop analysis
TechSource Systems Pte Ltd

Linearization

Objective: Discuss techniques for linearizing a Simulink model and validating the linearization results.

  • Linearization workflow
  • Operating points
  • Linearization functions
  • Frequency response estimation
TechSource Systems Pte Ltd
TechSource Systems Pte Ltd

PID Control in Simulink

Objective: Use Simulink to model and tune PID controllers.

  • PID Workflow
  • Model setup
  • PID Controller block
  • Automatic tuning
  • Additional PID features

Classical Control Design

Objective: Use classical control design techniques to develop system controllers. Common control techniques are covered, such as PID and lead/lag controllers.

  • Open-loop tuning
  • Closed-loop analysis
  • PID control
  • Lead-lag control
TechSource Systems Pte Ltd
TechSource Systems Pte Ltd

Response Optimization

Objective: Use optimization techniques to tune model parameters based on design requirements and parameter uncertainty.

  • Optimizing model response
  • Performing sensitivity analysis
  • Optimizing with parameter uncertainty

Controller Implementation

Objective: Discuss steps that might be needed to effectively implement a controller on a real system.

  • Identifying physical and practical limitations of controllers
  • Discretizing a controller
  • Preparing a controller for code generation
  • Converting to fixed-point data types
TechSource Systems Pte Ltd
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