Papers
3
Total Citations
45
H-Index
3
About
Khadidja Benzemrane is a researcher specializing in control systems, nonlinear observer design, and autonomous aerial vehicles. Her work focuses primarily on developing sophisticated estimation and control strategies for Unmanned Aerial Vehicles (UAVs), with particular emphasis on GPS-free navigation solutions — a critically important challenge for indoor applications and GPS-denied environments. Her most influential contribution, "Unmanned Aerial Vehicle Speed Estimation via Nonlinear Adaptive Observers" (2007), garnered 37 citations and addressed the fundamental problem of estimating UAV velocity using only onboard inertial sensors, without reliance on GPS infrastructure. Centered on a four-rotor helicopter prototype, this work demonstrated how nonlinear adaptive observer frameworks could deliver reliable state estimation under real-world constraints. She extended this research in her 2011 study on robust state observer design, further refining strategies for both indoor and outdoor UAV operations. Benzemrane's 2008 work bridging adaptive observer techniques with Kalman filtering reflects her broader interest in integrating classical and modern estimation methodologies. Her research has contributed meaningfully to the autonomous systems community, offering practical solutions that inform the design of more resilient, sensor-efficient UAVs — work that remains relevant as autonomous aerial systems continue to evolve across industrial, civilian, and research domains.
Research Focus
Key Achievements
Top Papers
- 1Unmanned Aerial Vehicle Speed Estimation via Nonlinear Adaptive Observers37 citations · 2007
- 2Nonlinear speed estimation of a GPS-free UAV4 citations · 2011
- 3Adaptive Observer and Kalman Filtering4 citations · 2008