Saeed Khorashadizadeh
Papers
27
Total Citations
875
H-Index
20
About
Saeed Khorashadizadeh is a prominent researcher specializing in robust and adaptive control of robotic systems, with particular expertise in uncertainty estimation, function approximation techniques, and intelligent control strategies for robot manipulators. His work has garnered over 530 citations, reflecting substantial influence in the robotics and control engineering communities. Khorashadizadeh's most significant contributions center on developing model-free and voltage-based control frameworks for electrically driven robots, addressing the perennial challenge of system uncertainty. A hallmark of his research is the innovative application of mathematical approximation tools — including Fourier series expansions, Legendre polynomials, Bernstein polynomials, and Szász–Mirakyan operators — as universal approximators to estimate and compensate for lumped uncertainties, unmodeled dynamics, and external disturbances. His 2012 paper on adaptive fuzzy uncertainty estimation remains his most impactful work with 105 citations. Beyond joint-space control, Khorashadizadeh has made notable advances in task-space and impedance control, eliminating the need for computationally expensive inverse kinematics. His more recent work extends into multi-robot systems, demonstrating adaptive formation control using reinforcement learning. Collectively, his research offers practical, implementable solutions that bridge theoretical rigor with real-world robotic applications.
Research Focus
Key Achievements
Top Papers
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- 7Optimal robust voltage control of electrically driven robot manipulators46 citations · 2012
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