Raaed F. Hassan

About

Raaed F. Hassan is a researcher whose work sits at the intersection of robotics, control systems, and optimization algorithms. His most cited paper, "PSO-based optimized neural network PID control approach for a four wheeled omnidirectional mobile robot" (2022), has garnered 31 citations and addresses the growing demand for automation by enhancing the precision of omnidirectional mobile robots—a key technology for applications inaccessible to humans. By integrating particle swarm optimization with neural network-tuned PID controllers, Hassan offers a sophisticated solution for improving robotic stability and maneuverability. Earlier, in 2013, he explored the design of Finite Impulse Response filters using genetic algorithms, demonstrating a sustained interest in bio-inspired computing for engineering challenges. While his citation count reflects a developing career, the practical relevance of his robotics work—particularly in automation and mobile systems—marks him as a contributor to advancing intelligent control. His research appeals to students and engineers seeking efficient, algorithm-driven approaches to real-world robotic navigation and signal processing.

Research Focus

Key Achievements

Top Papers

1. 1
   PSO-based optimized neural network PID control approach for a four wheeled omnidirectional mobile robot

   31 citations · 2022
2. 2
   Design of Finite Impulse Response Filters Based on Genetic Algorithm

   5 citations · 2013

Key Collaborators

Contact & Links