Wojciech Paszke
University of Zielona Góra, Eindhoven University of Technology
Papers
12
Total Citations
764
H-Index
7
About
Wojciech Paszke is a prominent control systems researcher whose work centers on iterative learning control (ILC), with particular expertise in handling the practical challenges that arise when deploying these algorithms in real-world settings. His most influential contributions address fundamental limitations of classical ILC frameworks, including nonuniform trial lengths, input constraints, and communication-constrained environments. His 2022 paper on optimal ILC for systems with nonuniform trial lengths has accumulated an remarkable 235 citations, reflecting its significance to the field, while his 2023 work integrating Q-learning with fault-tolerant ILC for MIMO systems has attracted 163 citations, demonstrating his forward-looking interest in merging machine learning with classical control theory. His 2024 research on quantized ILC with encoding and decoding mechanisms addresses critical bandwidth limitations in networked control systems, further broadening the applicability of ILC methods. Earlier work, including a 2013 study on robust finite frequency range ILC design and a 2009 experimental verification on a gantry robot, established his reputation for bridging rigorous theoretical development with physical implementation. Collectively, Paszke's portfolio showcases a researcher deeply committed to making learning control methods robust, practical, and deployable across diverse industrial applications.
Research Focus
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Top Papers
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