Teaching Control Systems with MATLAB and Simulink

With MATLAB and Simulink, you can:

Equip students with industry-relevant skills, preparing them for successful control engineering careers at renowned engineering companies that rely on these tools for control system development
Engage students with interactive lectures using MATLAB live scripts that combine explanatory text, mathematical equations, code, and results
Save time on course preparation by leveraging ready-to-use courseware, allowing you to focus more on teaching
Bridge the gap between theory and practice with project-based learning, equipping students with the practical skills needed in the industry
Facilitate independent learning with free self-paced interactive tutorials that help students get up to speed on MATLAB, Simulink, control design, and more
Save time by automatically grading student assignments in any learning environment

“MATLAB and Simulink have been instrumental in ... adopting a more student-centered approach to learning and enabling students to work on real problems with professional tools so that they are better prepared for careers in engineering.”

Industry Examples

Teaching Avionics and Control with a Minidrone Competition

Preparing Industry-Ready Engineers: Control Systems for Electric Vehicles (28:25)

From Student Competition to Industry Professional: Amine Taoudi's Road to Success at NXP Semiconductors

See more examples

Control Systems Course Topics

Getting Started with Simulink for a Control System

Introduction to Controls

With MATLAB and Simulink, you can teach control systems in an interactive and engaging way. Simulink provides a block diagram environment for modeling and simulating dynamic systems, making it easier for students to interactively design control systems and evaluate their performance. Using control apps from Control System Toolbox and Simulink Control Design, students can tune PID controllers and lead/lag compensators using interactive Bode and root locus editors.

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Estimation and System Identification

You can supplement classroom instruction with available resources for teaching estimation and system identification topics. You can use MATLAB Tech Talks to familiarize your students with these concepts before class. Also, you can use virtual labs, such as the Kalman filter virtual lab, so students can practice concepts through interactive exercises.

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Teaching Deep Reinforcement Learning with MATLAB

Advanced Control Systems

You can introduce your students to advanced control techniques, such as adaptive control, robust control, optimal control, and AI-based control, using Simulink Control Design, Fuzzy Logic Toolbox, Robust Control Toolbox, Model Predictive Control Toolbox, and Reinforcement Learning Toolbox. Students can manually implement various control algorithms and benchmark them against pre-built algorithms available in MATLAB and Simulink. These pre-built algorithms allow students to test and compare different control methods, enhancing their understanding of the strengths and limitations of the different approaches.

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Control System Labs

Support for low-cost hardware, such as Arduino, Raspberry Pi, and LEGO Mindstorms, allows students to apply theoretical concepts to practice, enhancing their understanding of control systems. You can introduce students to virtual labs in MATLAB and Simulink, where they can simulate and experiment with control systems in a safe environment. This provides a flexible and accessible platform to reinforce their learning.

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Applied Controls

You can use MATLAB and Simulink challenge projects to help your students develop practical skills by solving engineering problems across various industries, such as automotive, aerospace, robotics, and process control.

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