Gholamreza Nazmara
University of Shahrood, Imam Reza International University, Universidade do Porto
Papers
7
Total Citations
92
H-Index
6
About
Gholamreza Nazmara is a control systems researcher whose work centers on advanced robotics control, adaptive control theory, and human-robot-environment interaction. His scholarship is distinguished by a sustained focus on impedance control frameworks, fuzzy uncertainty estimation, and intelligent learning-based controllers for robotic manipulators operating under real-world uncertainties. Nazmara's most influential contribution, "Compound FAT-based prespecified performance learning control of robotic manipulators with actuator dynamics" (2022, 35 citations), exemplifies his expertise in function approximation techniques and performance-guaranteed control design. His pioneering work on regressor-free adaptive fuzzy impedance control addresses both parametric and non-parametric uncertainties using gradient descent algorithms, reflecting a sophisticated grasp of how robots interact with unknown environments. Across multiple papers, he has consistently advanced voltage-based control architectures that account for actuator dynamics — a practically important but often overlooked dimension in robotics research. More recently, Nazmara has extended his expertise toward underactuated marine robots, developing safe adaptive backstepping controllers suited for complex oceanic environments. With a growing citation record spanning foundational and emerging topics, his research offers students and engineers robust theoretical tools and practically deployable algorithms for next-generation autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6A Robust Adaptive Impedance Control of Robots8 citations · 2018
- 7Safe Robust Adaptive Motion Control for Underactuated Marine Robots4 citations · 2024