Rabah Mellah
Papers
7
Total Citations
61
H-Index
4
About
Rabah Mellah is a robotics and control systems researcher whose work bridges intelligent control, mobile robotics, and teleoperation. His primary research areas include real-time fuzzy control, adaptive neuro-fuzzy systems, and trajectory tracking for differential drive mobile robots. Mellah’s most cited work (26 citations) introduces a real-time Fuzzy-PID controller for mobile robot navigation and vision-based obstacle avoidance, demonstrating how fuzzy logic can enhance conventional PID control in complex, dynamic environments. He has also advanced feedback linearization techniques by incorporating dynamic models—rather than relying solely on kinematics—for improved trajectory tracking (11 citations). In the domain of bilateral teleoperation, Mellah developed a compensatory neuro-fuzzy controller that ensures synchronized position and force tracking between master and slave manipulators, combining neural networks with fuzzy logic for adaptive compensation. His broader contributions include environment mapping, collision avoidance, and real-time speed control for mobile robots. With a publication record spanning from 2015 to 2022, Mellah’s work is particularly valuable for researchers interested in intelligent control architectures that operate reliably under real-world uncertainties, offering practical solutions for autonomous navigation and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Compensatory neuro-fuzzy control of bilateral teleoperation system9 citations · 2015
- 4Control Bilateral Teleoperation By Compensatory ANFIS5 citations · 2015
- 5
- 6Real-Time Speed Control of a Mobile Robot Using PID Controller4 citations · 2022
- 7Compensatory Adaptive Neural Fuzzy Inference System2 citations · 2021