Amir Shirdel

Amir Shirdel is a Researcher at the Faculty of Science and Engineering, focusing on advanced control systems and system identification techniques. His work spans various applications including industrial automation, process control, and energy systems.

Dr. Shirdel's research interests center around control theory and system identification, with specific expertise in:

• Handling structural disturbances in control systems
• Wiener model identification
• Sparse optimization techniques for system identification
• Fuzzy control systems for industrial applications
• Kernel-based methods for forecasting and optimization

His publication record shows a consistent research trajectory from 2014-2018, with a focus on addressing practical challenges in system identification and control design. His work often addresses real-world engineering problems such as overhead crane control, waste heat recovery in ships, and process control systems that must function reliably despite disturbances and outliers. His publications demonstrate increasing impact, with his 2015 fuzzy controller paper receiving 21 Scopus citations.

Dr. Shirdel has established strong research collaborations, particularly with Böling, J. and Toivonen, H., with multiple co-authored publications appearing in reputable venues including IFAC World Congress and journals like Journal of Process Control and Neural Computing and Applications.