Matthias Feldt
Papers
2
Total Citations
20
H-Index
2
About
Matthias Feldt is a researcher specializing in advanced control systems for high-speed robotics, with a particular focus on Parallel Kinematic Manipulators (PKM). His work addresses a critical challenge in modern automation: maintaining precision at high dynamic speeds despite inherent mechanical uncertainties and nonlinearities. Feldt’s major contribution lies in the innovative application of Iterative Learning Control (ILC) to PKM systems, a method that iteratively refines motion trajectories to enhance accuracy over repeated cycles. His most cited paper, “Application study on Iterative Learning Control of high speed motions for parallel robotic manipulator” (2006), has garnered 12 citations, underscoring its influence in the field. A closely related work with 8 citations further demonstrates the sustained interest in his approach. By bridging control theory and practical robotics, Feldt has provided a framework that improves the performance of high-speed manufacturing and assembly systems. His research is particularly valuable for engineers seeking to push the limits of robotic speed without sacrificing precision, making his work a foundational reference in the domain of iterative learning and parallel robotics.
Research Focus
Key Achievements
Top Papers
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