Training - Courses

SLCT: MATLAB and Simulink for Control Design Acceleration

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

Control system design overview
System modeling
System analysis
Control design
Controller implementation

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	Detailed course outline

Day 1 of 2
Control System Design Overview	Objective: 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 are 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
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 LTI Viewer DC motor analysis Automation of analysis tasks Open loop analysis

Day 2 of 2
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
Control Design	Objective: Use classical control design techniques to develop system controllers. Common control techniques are covered, such as PID and Lead/Lag controllers. PID control Lead/Lag control Parameter tuning in Simulink
Controller Implementation	Objective: Discuss steps that might be needed to effectively implement a controller on a real system. Physical and practical limitations of controllers Discretizing a controller Creating more realistic simulations

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 Length - 2 days