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TechSource Systems is MathWorks Authorised Reseller and Training Partner
Control System Design with
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!
Course
Highlights
This two-day course provides a general understanding of how to accelerate the design process for closed-loop control systems using Simulink®. Topics include:
- Control system design overview
- System modeling
- System analysis
- Control design
- Controller implementation
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.
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.
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
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
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
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
Linearization
Objective: Discuss techniques for linearizing a Simulink model and validating the linearization results.
- Linearization workflow
- Operating points
- Linearization functions
- Frequency response estimation
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
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
