Amir Saleki
Papers
2
Total Citations
42
H-Index
2
About
Amir Saleki is a researcher in robotics and control systems, with a focus on model-free control strategies for electrically driven robot manipulators. His work addresses the challenge of controlling complex robotic systems without requiring precise dynamic models or parameter identification. Saleki’s major contribution lies in developing an extended state observer (ESO)-based control framework that operates on a voltage control strategy, eliminating the need for dynamic equations of the robot or its motors. His most cited paper, "Model-free control of electrically driven robot manipulators using an extended state observer" (2020), has garnered 40 citations, reflecting its impact on simplifying and optimizing robotic control. In earlier work (2018), he introduced an optimized linear ESO approach, further advancing model-free control by parameter optimization. Saleki’s research is notable for bridging theoretical control design with practical implementation, offering a robust, computationally efficient solution for real-time robotic applications. His contributions are particularly valuable for students and researchers exploring adaptive, model-free methods in robotics, as they reduce dependency on system identification while maintaining high performance.
Research Focus
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Top Papers
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