Papers
23
Total Citations
567
H-Index
9
About
Michael Ruderman is a prominent robotics and control systems researcher whose work has fundamentally advanced our understanding of elastic joint dynamics in robotic manipulators. His research focuses on modeling nonlinear mechanical phenomena — particularly hysteresis, backlash, friction, and torsional elasticity — that significantly affect the precision and reliability of robotic systems. Ruderman's most influential contribution, "Modeling and Identification of Elastic Robot Joints With Hysteresis and Backlash" (2009, 172 citations), established a landmark framework for capturing complex electromechanical behavior in geared robotic joints. Building on this foundation, he developed innovative sensorless control strategies, most notably the "virtual torsion sensor" concept (2015, 95 citations), enabling precise torsion control without dedicated hardware — a practically significant breakthrough for industrial robotics. His sustained productivity across compensation methods, observation techniques, and vibration control demonstrates a comprehensive research program spanning over a decade. Ruderman has also shaped the broader research community through editorial leadership in Industry 4.0 robotics and authored a dedicated text on kinetic friction compensation. With over 490 cumulative citations, his work remains essential reading for researchers tackling real-world nonlinearities in modern robotic and mechatronic systems.
Research Focus
Key Achievements
Top Papers
- 1Modeling and Identification of Elastic Robot Joints With Hysteresis and Backlash172 citations · 2009
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- 5Modeling and observation of hysteresis lost motion in elastic robot joints28 citations · 2012
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- 8Modeling of Elastic Robot Joints with Nonlinear Damping and Hysteresis20 citations · 2012
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