Farid Bourennani
Papers
1
Total Citations
3
H-Index
1
About
Dr. Farid Bourennani is a researcher whose work centers on intelligent control systems and robotics, with a particular focus on enhancing the autonomy and precision of wheeled mobile robots (WMRs). His most-cited contribution, "Trajectory Tracking of WMR with Neural Adaptive Correction" (2025, 3 citations), addresses a critical challenge in robotics: accurate trajectory tracking in dynamic environments. Bourennani proposes a novel neural adaptive correction technique that leverages machine learning to improve real-time control, enabling WMRs to navigate more reliably in sectors like logistics and transportation. This work demonstrates his ability to bridge theoretical control theory with practical robotic applications, offering a scalable solution for autonomous navigation. While his citation count is currently modest, the recency of his publication signals emerging impact in the field. Bourennani’s research is particularly relevant for students and engineers interested in the intersection of neural networks, adaptive control, and mobile robotics, as it provides a foundation for developing more resilient and intelligent robotic systems capable of operating in uncertain, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Trajectory Tracking of WMR with Neural Adaptive Correction3 citations · 2025