Mahdi Fazeli

Isfahan University of Technology, Sharif University of Technology

Papers

Total Citations

H-Index

About

Mahdi Fazeli’s research spans the intersection of robotics, control systems, and fault-tolerant computing, with a focus on enhancing reliability and precision in industrial applications. His most-cited work, “Adaptive hybrid position/force control for grinding applications” (2012, 8 citations), tackles a critical challenge in robotic manipulation: maintaining stable and accurate contact with uneven surfaces during grinding. By proposing an adaptive control strategy, Fazeli prevents workpiece damage and surface irregularities, directly improving manufacturing quality. In earlier foundational work, “A Solution to Single Point of Failure Using Voter Replication and Disagreement Detection” (2006, 5 citations), he addresses a key vulnerability in triple-modular redundant (TMR) systems used in robotics and industrial control. His distributed voting method employs time redundancy and disagreement detection to mask faults, eliminating single points of failure without compromising performance. These contributions demonstrate Fazeli’s dual expertise in real-time control adaptation and system-level fault tolerance—two pillars of dependable autonomous operation. His research offers practical solutions for industries requiring both precision and resilience, making him a notable figure in advancing robotic reliability for manufacturing and safety-critical environments.