Speaker: Mr. Abdullah Memon, Graduate Student of Control and Instrumentation Engineering Department

Abstract:

Modern power conversion systems, such as those used in Electric Vehicle (EV) charging and renewable energy applications demand high efficiency, stability, and robust performance under varying operating conditions. LLC Resonant Converter has emerged as a preferred topology due to its efficiency and soft switching characteristics. However, achieving optimal control in LLC converter remains challenging, especially under disturbances and dynamic load variations. This research provides a thorough analysis of the LLC resonant converter's physical modeling, design, and control using MATLAB Simulink (R2024a). Distinct control strategies, Active Disturbance Rejection Controller (ADRC), Proportional-Integral-Derivative (PID), PI, and PI-PD controller, have been implemented and rigorously analyzed under varying operational conditions. The investigation encompassed dynamic response, stability, and disturbance rejection capabilities of each controller. The results consistently demonstrated the superiority of the ADRC in comparison to PID family controllers, highlighting enhanced transient response, reduced overshoot, and improved robustness across diverse scenarios. The conclusion drawn from this study supports the efficacy of ADRC in LLC resonant converters, providing valuable insights into the selection of control strategies for optimal performance in practical applications.

Speaker Bio:

Mr. Abdullah Memon received his bachelor’s degree in Electronics Engineering from Mehran University of Engineering and Technology (MUET), Pakistan in 2022. Currently, he is pursuing an MS in Systems and Control Engineering program from the Control and Instrumentation Engineering Department at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. He has one published paper titled "Autonomous Farming Robot" based on his Final Year Project (FYP), which focused on embedded systems and IOT. His research interests include control systems, adaptive control, systems identification , and optimization algorithms. Currently, his focus is on renewable energy sources and their parameter estimation using predictive techniques.

All Faculty, Researchers, and Graduate Students are invited to attend.