Marquette integrated Model-Based Design with MATLAB® and Simulink® into multidisciplinary engineering system design courses in all four undergraduate years.
First-year students take Engineering Discovery 1, in which they model, simulate, and analyze basic electrical, mechanical, fluid, thermal, and electromechanical systems using MATLAB and Simulink, and then validate their models with hardware experiments.
In Engineering Discovery 2, students apply the same modeling and simulation approach, as well as computer programming in MATLAB, to energy-related products, systems, and processes.
In the second year, the focus shifts to discipline-specific courses. Mechanical engineering students in Electromechanical Engineering Systems use MATLAB and Simulink to model simple electrical systems made up of resistors and capacitors. Via simulation they explore the effects of undersampling on aliasing. They then compare simulation results with measurements taken on actual circuits in the lab.
In the same course, students study basic controller design and model a proportional-integral controller for an RC circuit. Using Simulink Coder™ they generate code from their model and run it on an Arduino® microcontroller, comparing the results on the lab oscilloscope with the simulation results.
In the third-year course Multidisciplinary Engineering Systems, the students use Model-Based Design to develop classical controls for thermal, electromechanical, and fluid power systems. They design the controllers using root locus and frequency response techniques with Control System Toolbox™. They are introduced to Simscape Electrical®, Simscape Fluids™, and Simscape Multibody™ for modeling physical systems, and are encouraged to use these products on their own.
In the Mechatronics course, fourth-year students design and build a two-wheeled self-balancing transporter. They use MATLAB and Simulink to model the mechanical structure, motors, sensors, and control electronics. With System Identification Toolbox™ they estimate friction and other system parameters.
The linear quadratic regulator control for balancing the transporter is developed in MATLAB, and the proportional-integral-derivative control for steering and forward-backward motion is developed using Simulink Control Design™. Students automatically generate control, sensing, and RF communication code from their Simulink model for deployment on an Arduino microcontroller.
Fourth-year students also use Model-Based Design for capstone design projects, which often involve partnering with local companies.