Svante Gunnarsson
Papers
38
Total Citations
1,116
H-Index
16
About
Svante Gunnarsson is a prominent Swedish control systems researcher whose work sits at the intersection of iterative learning control (ILC), system identification, and industrial robotics. His most influential contribution, "On the design of ILC algorithms using optimization" (2001, 292 citations), established a rigorous optimization-based framework that has become foundational in the ILC field. Complementing this theoretical work, Gunnarsson has consistently grounded his research in real-world applications, particularly through extensive collaboration with ABB to evaluate control and identification methods on commercial industrial robots. His contributions to robot system identification are substantial, spanning nonlinear effects in frequency-domain analysis, backlash in transmissions, friction modeling under varying load and temperature conditions, and closed-loop identification of flexible robot structures. More recently, his research has expanded into data-driven diagnostics, applying machine learning and statistical modeling to gearbox fault detection and failure prediction in robotic arms, with his 2019 paper on hybrid gradient boosting accumulating 60 citations. Across a career spanning over two decades, Gunnarsson has consistently bridged rigorous mathematical theory with industrial application, making him a significant figure for researchers working on advanced control and diagnostics in robotics and automation.
Research Focus
Key Achievements
Top Papers
- 1On the design of ILC algorithms using optimization292 citations · 2001
- 2Closed-loop identification of an industrial robot containing flexibilities110 citations · 2003
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- 6NONLINEAR IDENTIFICATION OF A PHYSICALLY PARAMETERIZED ROBOT MODEL 150 citations · 2006
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- 9A framework for analysis of observer‐based ILC36 citations · 2010
- 10Nonlinear identification of backlash in robot transmissions29 citations · 2002