Oussama Bouaiss
Papers
1
Total Citations
8
H-Index
1
About
Oussama Bouaiss is a leading researcher in intelligent control systems, with a primary focus on adaptive neural network-based strategies for unmanned aerial vehicles (UAVs), particularly quadrotors. His most cited work, "Adaptive neural network based compensation control of quadrotor for robust trajectory tracking" (2023, 8 citations), introduces a pioneering nested control framework that integrates adaptive radial basis function neural networks (RBFNN) with integrator backstepping (IBS) to achieve robust trajectory tracking under uncertainty. This contribution addresses critical challenges in nonlinear dynamics and external disturbances, offering a computationally efficient solution that enhances stability and precision in real-time flight. Bouaiss’s research bridges theoretical advances in neural network control with practical UAV applications, demonstrating significant impact in the growing field of autonomous systems. His work is recognized for its potential to improve safety and performance in drone operations, from surveillance to delivery. By combining adaptive compensation with supervisory learning, Bouaiss continues to shape the next generation of resilient, intelligent aerial robotics.
Research Focus
Key Achievements
Top Papers
- 1