“MATLAB and Simulink make it easy for students and professors alike to develop algorithms, design systems, and then visualize the results. We can change a parameter and immediately see the effect. When we are happy with the model, we generate code with confidence that it will work as designed, with no errors.”
Dr. Paule Blanchart, École Centrale de Lyon
École Centrale de Lyon’s top-ranked engineering program is founded on three core principles: to combine theoretical training and learning by doing through an emphasis on classroom work, projects, and internships; to promote learning through research; and to balance individual and group work to foster autonomy and collaboration skills.
To help meet these objectives across a multidisciplinary curriculum, École Centrale de Lyon faculty have integrated MathWorks tools into the engineering program, including lectures and lab assignments, student competitions, and faculty-led research initiatives.
“One of the great benefits of MathWorks tools is that students can immediately see results via simulation,” notes Dr. Paule Blanchart, senior lecturer at École Centrale de Lyon. “They can then generate code for a prototype and have confidence that the prototype will perform as their model did in simulation.”
“Though they study mathematics and physics in preparatory school, our incoming students have not put theory into practice,” says Blanchart. To help students connect engineering principles and real-world applications, École Centrale de Lyon faculty wanted them to have easy access to tools for numerical analysis, modeling, simulation, and prototyping.
“In the past, professors would write programs to introduce students to new concepts, such as numerical filters,” says Blanchart. “It took a long time to write the programs, and even more time to make them compatible with different platforms. We wanted to simplify this process, and let the students experiment with tools they will use after graduation, in engineering firms.”
École Centrale de Lyon acquired a Total Academic Headcount (TAH) license, which enables students and faculty to use 50 MathWorks products anywhere on campus.
The first-year Signals and Systems course introduces new concepts using MATLAB®. In directed works, the students then use MATLAB to complete exercises on correlation, convolution, fast Fourier transforms, and other topics.
The students use Simulink® to design signal processing chains. After adding signal generator, filter, mux, and sum blocks to the design, the students select the sampling time and specify filter parameters before observing the signal at various points using a Scope block. The students write MATLAB scripts to process simulation results and then discuss their observations.
For the French Robotics Cup (la Coupe de France de Robotique), Blanchart’s students used MathWorks products to design and build an autonomous robot. They developed control algorithms with MATLAB, Stateflow®, Control System Toolbox™, and Robust Control Toolbox™, and modeled the motor and sensors with Simulink, Stateflow, and Simscape™. Using Simulink 3D Animation™, the students visualized how the robot would move.
After running simulations to debug and verify the design, they used Stateflow and Simulink Coder™ to generate 2000 lines of C code, which was compiled and deployed on the robot’s onboard processor.
Blanchart and her colleagues also use MathWorks tools extensively in their research.
On one project, Blanchart developed a bracelet for the elderly that summons help in the event of a fall. She and her students used MATLAB, Fuzzy Logic Toolbox™, Partial Differential Equation Toolbox™, and Curve Fitting Toolbox™ to develop algorithms that processed data from the bracelets’ accelerometers to detect falls. The students verified the system by processing video data of simulated falls using Image Processing Toolbox™.
On another project, Blanchart worked with students and local musicians to develop a numerical filter using MATLAB, Simulink, and Signal Processing Toolbox™. The bass guitarist chooses the filter type (lowpass, highpass, or bandpass), and the cutoff frequency changes with the rhythm provided by the bass guitarist.
With MATLAB, they prototyped the signal acquisition chain for a MIDI bass anti-aliasing filter and selected the sampling frequency and converter. They then generated code for a Texas Instruments C6000™ DSP using Simulink Coder.
Provide engineering students with a foundation that links theory and practical experience
Standardize on MathWorks tools in a multidisciplinary engineering curriculum that emphasizes hands-on work in class, student competitions, and research