This is an online, interactive lab that contains instructions, multimedia, and assessments where students can learn at their own pace. As an instructor, you can create and edit instances of this lab, assign them to students, and view student progress.
This is an online, interactive course that contains instructions, multimedia, and assessments where students can learn at their own pace. As an instructor, you can create and edit instances of this course, assign them to students, and view student progress.
Controlling the speed of a DC motor is one of the most common tasks that automation, robotics, and industrial engineers are called upon to perform when creating industrial systems. In this lab students will learn the fundamentals of qualitative and quantitative PI control design. They will then implement a controller and analyze the data through a series of short calculations and short answer questions. The skills gained in these exercises are directly applicable to a multitude of exciting emerging application areas in engineering.
After completing this lab, students will be able to:
Tune PI control parameters for speed control of a DC motor.
Design PI control parameters to meet speed control specifications.
Use lead compensator design to control the speed of a DC motor.
REQUIRED SKILLS
Differential Equations or equivalent
Linear Algebra or equivalent
Dynamic Systems or equivalent
Basic LabVIEW Proficiency
Requirements
NI ELVIS III
Engineering laboratory solution for project-based learning that combines instrumentation and embedded design with a web-driven experience, delivering a greater understanding of engineering fundamentals and system design.
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Quanser Controls Board for NI ELVIS III
The Quanser Controls Application Board is a versatile servo system designed to teach the fundamentals of DC motor control, with an optional pendulum module to teach advanced topics in non-linear control.
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LabVIEW
LabVIEW is systems engineering software for applications that require test, measurement, and control with rapid access to hardware and data insights.
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