Papers
18
Total Citations
361
H-Index
11
About
Didier Dumur is a prominent control systems and robotics researcher whose work has significantly advanced the fields of predictive control, robust motion control, and robot manipulator dynamics. His research spans several interconnected areas, including H∞ control design for elastic-joint robots, nonlinear predictive control strategies, and reliability assessment of robotic systems. Among his most influential contributions is a 2016 paper (85 citations) introducing a novel model-based H∞ preview control framework for flexible-joint robots operating under model uncertainties—a landmark advance for practical industrial robotics. His earlier foundational work on nonlinear predictive control, including Taylor approximation-based finite-horizon methods and continuous-time predictive schemes for rigid-link manipulators, established key theoretical and applied frameworks widely referenced in the control community. Dumur has also made meaningful contributions to human-robot interaction safety, developing proprioceptive impact detection methods robust to model uncertainties (48 citations), and to multi-objective optimal robot design incorporating workspace and energy criteria. His more recent explorations into fuzzy-based kinematic reliability assessment reflect a growing interest in uncertainty quantification for robotic systems. With a portfolio spanning over two decades and hundreds of cumulative citations, Dumur's work remains a valuable reference for researchers working at the intersection of advanced control theory and robotic systems engineering.
Research Focus
Key Achievements
Top Papers
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- 4Feedback nonlinear predictive control of rigid link robot manipulators29 citations · 2002
- 5Multi-objective optimal design of flexible-joint parallel robot24 citations · 2018
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- 8ANALYSIS OF FRACTIONAL - ORDER ROBOT AXIS DYNAMICS18 citations · 2006
- 9Robot Axis Dynamics Control Using A Virtual Robotics Environment13 citations · 2006
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