Khaled Telli
Papers
1
Total Citations
2
H-Index
1
About
Dr. Khaled Telli is an emerging researcher in the field of unmanned aerial vehicle (UAV) dynamics and intelligent control systems, with a particular focus on quadrotor modeling and neural network-based identification. His most cited work, "Quadrotor Experimental Dynamic Identification with Comprehensive NARX Neural Networks" (2023), addresses the critical challenge of accurately modeling quadrotor systems, which are inherently nonlinear, underactuated, and multivariable. By leveraging Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networks, Dr. Telli’s research provides a robust framework for capturing complex dynamic behaviors that traditional linear models fail to represent. This contribution is vital for advancing autonomous flight control, enabling more precise and adaptive UAV performance in real-world applications. Although his citation count is currently modest, his work represents a foundational step toward integrating machine learning with aerospace engineering. Dr. Telli’s research holds promise for students and engineers seeking to bridge the gap between theoretical control systems and practical quadrotor deployment, marking him as a rising voice in intelligent aerial robotics.
Research Focus
Key Achievements
Top Papers
- 1