Payam Kheirkhahan
Papers
11
Total Citations
205
H-Index
8
About
Payam Kheirkhahan is a control systems researcher whose work centers on advanced robotics control, with particular expertise in adaptive control, fractional-order systems, and intelligent estimation techniques for electrically driven robot manipulators. His research has made meaningful strides in addressing the longstanding challenges of uncertainty, nonlinearity, and model dependency in robotic control systems. Among his most significant contributions is the development of Function Approximation Technique (FAT)-based and Fourier series-based controllers that eliminate the need for complex regressor matrix computations, substantially simplifying real-time implementation. His 2018 paper on FAT-based robust adaptive impedance control has garnered 33 citations, while his investigations into fractional-order control strategies—both adaptive and fuzzy—collectively demonstrate a sustained effort to enhance precision and robustness in flexible-joint robots operating under realistic conditions. Notably, his model-free observer for velocity estimation (26 citations) addresses a critical practical limitation in robot control by removing dependence on system dynamics knowledge. Kheirkhahan has also contributed to the research community through rigorous peer critique, identifying stability proof errors and analytical shortcomings in existing literature. With over 180 total citations across his published work, his research offers both theoretical depth and experimental validation, making him a valuable reference for students and engineers working at the intersection of control theory and robotics.
Research Focus
Key Achievements
Top Papers
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- 4Tracking Control of Electrically Driven Robots Using a Model-free Observer26 citations · 2018
- 5On the Voltage-based Control of Robot Manipulators Revisited22 citations · 2018
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