Morten Kjeld Ebbesen
Papers
2
Total Citations
5
H-Index
2
About
Morten Kjeld Ebbesen is a researcher whose work centers on the modelling, simulation, and control of robotic manipulators, with a particular emphasis on flexible structures and adaptive learning systems. His key contributions include the development of a dynamic model for two-link flexible robots using Rayleigh beam theory and the Lagrangian formulation, a study that has garnered 3 citations since 2023. This work provides a foundational framework for understanding the complex vibrational behaviour of lightweight, flexible manipulators. More recently, Ebbesen has advanced the field of intelligent control by proposing a decentralised, learning-based Adaptive Dynamic Programming (ADP) approach for robot manipulators with unknown parameters. This 2025 paper, with 2 citations, addresses the critical challenge of controlling multi-degree-of-freedom systems without precise prior knowledge of their dynamics, offering a path toward more autonomous and adaptable robotic systems. By combining rigorous structural modelling with cutting-edge reinforcement learning techniques, Ebbesen’s research bridges the gap between theoretical mechanics and practical, data-driven control, making significant strides toward more efficient and intelligent robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1
- 2