Shawkat K. Guirguis

Papers

Total Citations

H-Index

About

Shawkat K. Guirguis is a researcher whose work lies at the intersection of intelligent control systems and robotics, with a particular focus on hybrid neural and fuzzy logic architectures. His most-cited paper, "Hybrid Neural Predictive-Fuzzy Controller for Motorized Robot Arm" (2011, 5 citations), introduces a novel design methodology that synergistically combines neural predictive control with fuzzy logic to create a more robust and adaptive controller for robotic manipulators. This work demonstrates his core contribution: developing intelligent control strategies that leverage the strengths of multiple AI paradigms to improve system performance in complex, real-world environments. While his citation count reflects a specialized, emerging area of research, Guirguis’s approach is notable for its practical engineering focus—aiming to bridge theoretical advances in computational intelligence with tangible applications in automation and robotics. His work offers a valuable foundation for students and researchers exploring hybrid control systems, particularly those interested in enhancing the precision and adaptability of motorized robotic arms through integrated neural and fuzzy methodologies.