Donald Ebeigbe
Papers
5
Total Citations
55
H-Index
4
About
Donald Ebeigbe is a leading researcher in the control of robotic systems, with a primary focus on advanced control theory for rigid robots and prosthetic devices. His work centers on developing regressor-free and function approximation technique (FAT)-based controllers, which eliminate the need for exact dynamic models—a critical advancement for real-world robotic applications. Ebeigbe’s major contributions include the creation of robust, hybrid, and passivity-based adaptive controllers, such as the novel APFAT controller, which simplifies design while ensuring stability and performance. His most cited paper, "Robust Regressor-Free Control of Rigid Robots Using Function Approximations" (2019, 21 citations), establishes a foundational framework for controlling Euler-Lagrange systems without regressor matrices. Additionally, his work on hybrid control for prosthetic legs (2016, 11 citations) directly impacts assistive technology, while his 2017 paper on robotics and prosthetics at Cleveland State University highlights his role in bridging modern information and communication technologies with rehabilitation engineering. Ebeigbe’s research has garnered over 55 citations, reflecting its influence on both theoretical control design and practical robotic applications.
Research Focus
Key Achievements
Top Papers
- 1Robust Regressor-Free Control of Rigid Robots Using Function Approximations21 citations · 2019
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