Research Projects

Designing a nonlinear controller to ensure stability for motors with nonlinear characteristics 

Designing an optimal controller by considering a system with nonlinear features in linear parameter varying (LPV) form 

 Physical modelling to describe the dynamic characteristics of the system using data from the target for identification purposes

Apply existing model-based control theory through data-driven system identification

Performance analysis of systems subject to communication delays and external disturbances  

Development of control algorithm considering the dynamic characteristics of robots with time delays 

Reinforcement learning application for enhanced tracking performance through the estimation of time delays 

Power system simulation Including DER for big data acquisition 

Feature analysis for fault detection using machine learning (Support Vector Machine, Logistic Regression)  

Tuning techniques for effective learning in artificial intelligence