Arman Beiranvand
Papers
3
Total Citations
38
H-Index
3
About
Arman Beiranvand is a researcher whose work sits at the intersection of precision robotics, advanced sensing, and nonlinear control. His primary research areas include the design of novel force sensors, the dynamic modeling of robotic systems, and the development of robust control strategies. Beiranvand’s major contributions are exemplified by his work on a multi-axis force sensor based on the Hall effect, which features a decoupled structure for enhanced accuracy—a paper that has garnered 18 citations. He has also made significant strides in the control of parallel robots, where he proposed a minimum length integral sliding mode control approach that accounts for virtual flexible links, a study cited 17 times. This work addresses the critical challenge of modeling and identifying robot dynamics, particularly the influence of prismatic joints and variable friction, to achieve high-precision performance. Beiranvand’s research is notable for its practical focus on improving the fidelity of dynamic models, directly impacting the quality of control implementation in complex robotic systems. His contributions are valuable for engineers and researchers working on the frontier of mechatronics and precision motion control.
Research Focus
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