Murad Samhouri

Queen's University

Papers

1

Total Citations

10

H-Index

1

About

Murad Samhouri is a researcher specializing in intelligent control systems, robotics, and neuro-fuzzy applications for industrial automation. His work focuses on enhancing precision and adaptability in robotic systems, particularly through the integration of adaptive neuro-fuzzy inference systems (ANFIS) for controller tuning. His most-cited paper, "Control of a pneumatic gantry robot for grinding: a neuro-fuzzy approach to PID tuning" (2005, 10 citations), presents a novel method for optimizing PID gains using ANFIS to model the relationship between controller parameters and system response. This contribution addresses a practical challenge in manufacturing—grinding steel blanks with pneumatic robots—by improving accuracy and reducing manual calibration. While his citation count reflects focused impact in specialized domains, Samhouri’s work bridges theoretical control engineering with real-world automation, offering a framework for adaptive tuning that can be extended to other robotic and mechatronic systems. His research is valuable for students and engineers exploring intelligent control, fuzzy logic, and industrial robotics, demonstrating how hybrid AI techniques can enhance traditional PID control in complex, nonlinear environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Control of a pneumatic gantry robot for grinding: a neuro-fuzzy approach to PID tuning
10 citations · 2005
📈 Most Prolific Year: 2005 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Queen's University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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