Adaptation of the introductory control system laboratory apparatus for model based design

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Abstract

Model Based Design (MBD) has been enabling engineers to rapidly develop, test, analyze, and implement control system concepts. Many companies, especially in automotive and aerospace industries, have seen increases in design and development productivity and decreases in cost and time while retaining the quality of firmware in embedded systems. As MBD is becoming a trend in industries’ standard practice, it is important for the university education to adapt and integrate these tools into the students’ learning experience. The MBD approach enhances the deployment of complex control systems by abstracting their complexity into graphical representation of system models. The models support an array of analysis and simulation tools that permit the designer to progressively evaluate alternative control structures and components to reach the required performance requirements. The tools ultimately lead to the auto-generation of the source code for the embedded systems firmware. But it is important in the education context that students understand the engineering concepts underlying the tools and to not obscure too much of the backend information. To appreciate the automation of firmware generation students should have a minimal understanding of basic coding practices to maximize the learning outcome. This thesis presents the MBD methods used to automate the generation of new firmware of an existing laboratory apparatus called the MotorLab and to integrate MBD concepts into an undergraduate controls course. MotorLab is used in the introductory controls course at Alan Levin Department of Mechanical and Nuclear Engineering at Kansas State University. The updated firmware is carefully examined to ensure the full range of functionality of the original lab device to deliver the same effective lab exercises and to demonstrate the application and benefits of MBD.

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Keywords

Model based design, Education, Laboratory, Embedded control systems

Graduation Month

December

Degree

Master of Science

Department

Department of Mechanical and Nuclear Engineering

Major Professor

J. Garth Thompson; Warren N. White

Date

2021

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Thesis

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