Advanced Control Theory
Robust Nonlinear Control and Data-driven Control Design for ensuring system stability under uncertainty.
Welcome to COOL
Stable, intelligent and optimal systems.
We are a team of passionate researchers (“COOL Guys”) dedicated to designing the “Brain” of future mobility systems.
Our mission is to bridge the gap between Advanced Control Theory and Real-world Applications. We integrate robust control strategies with embedded AI to create systems that are stable, intelligent, and optimal.
At COOL, we don’t just stop at simulations. We emphasize end-to-end validation, from rigorous mathematical proofs to real-time implementation on actual hardware platforms.
01Mathematical proofLyapunov-based stability and robustness guarantees
02Controller & observer designDisturbance observers, adaptive and learning-based laws
03Simulation & HILSMATLAB/Simulink, SCALEXIO, MicroAutoBox, CarSim
04Real-time hardwareMotors, robots, drones, vehicles and edge platforms
Core research areas
Control theory that runs on real machines.
Robot & Mobility
Auto-learning-based control for Robotics, UAVs (Drones), and Defense Applications.
Physical AI & Learning
Light-weight AI (MLP-Mixer) and ESO-based Signal Augmentation on embedded systems for real-time processing.
Reinforcement Learning
Deep Koopman-based Model Predictive Control (MPC) and novel learning frameworks using Disturbance Observers.
Research topics
What we are working on.
Adaptive Neural Network Control
Intelligent control for highly uncertain and nonlinear dynamic systems. Neural networks identify and compensate unknown dynamics, external disturbances and time-varying changes online, while Lyapunov theory guarantees the stability and safety of the whole closed loop.
Advanced Control for Electric Motors (PMSM)
Field-Oriented Control frameworks for precise torque and speed regulation of permanent magnet synchronous motors, with Disturbance Observers and Event-Triggered Control to reject load variations and cut computation and bandwidth.
Intelligent Gain Tuning Techniques
Adaptive Learning Gain (ALG) algorithms for cascaded control systems. Update laws auto-tune control gains in real time to reach the desired tracking performance across trajectories, robust to unknown loads and parameter variations.
Intelligent Dual-Arm Robotic Manipulation
Low-level control of multi-DOF dual-arm cooperative manipulators: joint dynamics, precise torque regulation and high-frequency real-time execution, with robust impedance/admittance control for safe human-robot interaction, payload handling and collision avoidance.
Advanced Braking System Control (ABS) & HILS
Robust control of automotive hydraulic brakes, including ABS, validated on real brake hardware through Hardware-in-the-Loop Simulation with real-time targets (SCALEXIO) and MATLAB/Simulink, for slip regulation and stability on varied road friction.
Electric Power Steering (EPS) & Vehicle Dynamics
Lateral dynamics and active steering on a dedicated steering simulator with rapid control prototyping (MicroAutoBox, CarSim): steering assist that improves feel, handling precision and lateral safety for autonomous driving.
Data-Driven Control via Deep Koopman MPC
Deep neural networks lift nonlinear dynamics into a linear latent space, so efficient linear MPC can run on originally intractable systems, enabling real-time optimal control and trajectory planning of robotic manipulators from purely data-driven models.
Reinforcement Learning-based Robust Control
RL agents combined with Extended State Observers learn optimal policies for uncertain nonlinear systems while staying robust to unmodeled dynamics and disturbances, so AI-driven policies are safe and deployable on real hardware.
Members
The COOL Guys.
Director · Principal Investigator
Prof. Sesun You
유세선
- yousesun@inu.ac.kr
- Office
- Room 357, College of Engineering (Bldg. 8), Incheon National University
- Links
- Google Scholar ↗YouTube ↗
Education & career
- Assistant Professor, Incheon National UniversityDepartment of Electronic Engineering
- Assistant Professor, Keimyung UniversityDepartment of Electrical Engineering
- Ph.D., Chung-Ang UniversitySchool of Energy Systems Engineering
- B.S., Chung-Ang UniversitySchool of Energy Systems Engineering
Nonlinear ControlAdaptive ControlReinforcement-learning-based ControlOptimizationIndustrial Applications
Publications
Latest journal articles.
Patents
Registered patents.
Join the COOL team
Be COOL.
We are actively recruiting highly motivated M.S./Ph.D. students and Undergraduate Interns. We value strong fundamentals in dynamics, mathematics, and programming skills (MATLAB/Python). Above all, we look for intellectual curiosity and grit to solve unsolved problems.
When you contact Prof. You, please share a short story of your persistence. It doesn’t have to be academic: reaching Diamond Tier in LoL, completing a 50 km march or a full marathon, a successful diet diary. Anything that shows your tenacity is welcome.
If you are passionate about Control, AI, and Future Mobility, join us and be COOL.
What you will gain
Full-Stack MasteryFrom control theory to real-time embedded AI implementation (C/C++/Python, ROS2).
Tangible ExperienceBuild and test actual drones, robots, and edge computing platforms.
Industry LeadershipGrow into an expert who leads the automotive, robotics, and defense industries.
yousesun@inu.ac.krRoom 357, Building 8, Incheon National University