Peiman Naseradinmousavi
Papers
18
Total Citations
271
H-Index
10
About
Peiman Naseradinmousavi is a robotics and control systems researcher whose work has significantly advanced the science of high-degree-of-freedom (DOF) robot manipulation, with a particular focus on time delay compensation, adaptive control, and trajectory optimization. His most cited work, "Feedback Linearization Based Predictor for Time Delay Control of a High-DOF Robot Manipulator" (2019, 59 citations), established a foundational framework for addressing actuator delays in complex robotic systems — a persistent challenge in teleoperation and networked robotics. Building on this, he developed delay-adaptive and prescribed-time control strategies, experimentally verified on 7-DOF manipulators, demonstrating rigorous translation from theory to hardware. His contributions to trajectory optimization using multivariable extremum seeking and global sensitivity analyses have provided practical tools for energy-efficient robotic motion planning. More recently, Naseradinmousavi has pioneered prescribed-time safety filters for real-time obstacle avoidance and integrated deep learning-based autonomous 3D path planning into physical manipulator platforms. With over 225 total citations across his most influential works, his research bridges sophisticated mathematical control theory and experimental robotics, making him a compelling voice for students and engineers advancing autonomous and teleoperated robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Delay-Adaptive Control of a 7-DOF Robot Manipulator: Design and Experiments29 citations · 2022
- 3Adaptive control of a two-link robot using batch least-square identifier29 citations · 2021
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