Rabab Alaa Hameed

Papers

Total Citations

H-Index

About

Rabab Alaa Hameed is a researcher specializing in robotics, adaptive control systems, and artificial intelligence, with a particular focus on the motion control of nonlinear dynamic systems. Her most-cited work, "An adaptive neural control methodology design for dynamics mobile robot" (2022), introduces an innovative approach that combines adaptive artificial neural networks with an online-tuning evolutionary slice genetic algorithm. This methodology significantly enhances mobile robot performance during trajectory tracking in environments with static obstacles, demonstrating a practical fusion of machine learning and control theory. With 10 citations, this paper highlights her contribution to improving autonomous navigation and real-time adaptability in robotics. Hameed’s research is notable for bridging theoretical control design with real-world robotic applications, offering scalable solutions for dynamic and uncertain environments. Her work is particularly valuable for students and researchers interested in intelligent control systems, evolutionary algorithms, and the integration of neural networks into robotic platforms. Through her adaptive control strategies, Hameed continues to advance the field of mobile robotics, providing robust frameworks for autonomous systems.