Papers
34
Total Citations
485
H-Index
12
About
Musa Mailah is a prominent robotics and control systems researcher whose work spans intelligent control, force control strategies, robotic manipulation, and autonomous mobile systems. Over nearly three decades, he has made foundational contributions to Active Force Control (AFC), a robust disturbance-rejection framework he has persistently refined and applied across diverse platforms — from rigid robot arms and parallel manipulators to wheeled mobile robots and human-like arm models. Mailah's earliest highly cited work, dating to 1996, established AFC as an effective strategy for robot arm control, a theme he has continuously advanced by integrating intelligent techniques including fuzzy logic, neural networks, genetic algorithms, and iterative learning. His 2011 studies on parallel manipulators and pneumatic artificial muscles demonstrate his ability to tackle highly nonlinear, complex systems. More recently, his research has expanded into autonomous vehicle navigation, with sensor fusion and fuzzy logic-based systems enabling smart roundabout detection and road following, reflecting his adaptability to emerging robotics challenges. With his most-cited paper alone accumulating 62 citations and a collective body of work exceeding 340 citations across these ten papers, Mailah's research has meaningfully shaped intelligent robotic control, offering practical, computationally efficient solutions with real-world applications in industrial automation and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Intelligent active force control of a robot arm using fuzzy logic35 citations · 2002
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- 7Modelling and control of a human-like arm incorporating muscle models24 citations · 2009
- 8ACTIVE FORCE CONTROL APPLIED TO A RIGID ROBOT ARM23 citations · 1996
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