Amirmehdi Yazdani

Murdoch University, Flinders University, University of Utah

Papers

18

Total Citations

186

H-Index

9

About

Amirmehdi Yazdani is a robotics and control systems researcher whose work spans intelligent motor control, autonomous robotics, and human-robot interaction. Over more than a decade of contributions, he has established himself as a specialist in applying biologically inspired and adaptive control strategies to complex, uncertain dynamical systems. His early foundational work on brain emotional learning-based intelligent controllers (BELBIC) for stepper motors — beginning in 2012 and continuing through 2018 and 2019 — demonstrated how neuro-fuzzy and emotionally motivated learning architectures could achieve robust precision in highly nonlinear systems, accumulating nearly 70 citations across those studies alone. Yazdani's research has since expanded into autonomous underwater vehicles (AUVs) for ecological monitoring, robotic fish speed control using sliding mode techniques, and prescribed performance control of robotic manipulators under uncertainty. His work on the Kian-I mobile robot and ergonomically intelligent teleoperation systems reflects a broader commitment to real-world deployable robotics. With over 150 citations across his published works, Yazdani's research consistently bridges rigorous control theory with practical robotic applications, making his contributions particularly valuable for engineers and researchers working at the intersection of intelligent control and autonomous systems.

Research Focus

Key Achievements

9
H-Index
18
Papers
186
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Robust precise trajectory tracking of hybrid stepper motor using adaptive critic-based neuro-fuzzy controller
28 citations · 2019
📈 Most Prolific Year: 2021 (6 Papers)
🤝 Key Collaborators: 39
🏛 Institutions: Murdoch University, Flinders University, University of Utah

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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