Marcin Boski
Papers
1
Total Citations
3
H-Index
1
About
Dr. Marcin Boski is a control systems researcher whose work centers on iterative learning control (ILC) and repetitive process theory, with a particular focus on designing efficient, parameter-sparse algorithms for systems that repeat tasks. His most cited paper, “Repetitive Process Based Design of PD-Type Iterative Learning Control Laws” (2018), introduces a novel framework that combines proportional-derivative learning functions with state feedback, significantly reducing the number of parameters that require manual tuning. This approach extends the applicability of ILC to a broader class of industrial and robotic systems, where precision and ease of implementation are critical. With 3 citations, this work has laid a foundation for subsequent studies in repetitive process-based control design. Dr. Boski’s contributions are notable for bridging theoretical rigor with practical usability, offering engineers a streamlined method to improve tracking performance over successive iterations. His research continues to influence the development of learning-based control strategies, making him a valuable reference for students and researchers exploring advanced control theory and its real-world applications.
Research Focus
Key Achievements
Top Papers
- 1