Rabeh Abbassi
Papers
2
Total Citations
27
H-Index
2
About
Rabeh Abbassi is a researcher specializing in advanced neural network methods, robotics control, and nonlinear system dynamics. His work focuses on solving complex mathematical problems in real-time robotic applications, particularly through the development of higher-order zeroing neural networks. His most cited paper (2023, 16 citations) introduces novel approaches for calculating time-varying quaternion matrix inverses, a critical challenge in physics, engineering, and computer science, with direct applications to robotic motion tracking. Abbassi’s research addresses the practical difficulties of controlling flexible joint robot manipulators, as demonstrated in his 2022 work (11 citations) on fuzzy Luenberger observer design, which reduces the need for additional sensors by accounting for joint elasticity in control processes. His contributions bridge theoretical mathematics and applied robotics, offering efficient solutions to computationally intensive problems. With a growing citation record, Abbassi’s work is increasingly recognized for its impact on real-time robotic systems and nonlinear control, making him a notable figure in the intersection of neural computing and robotics engineering.
Research Focus
Key Achievements
Top Papers
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