Marzieh Yazdanzad
Papers
2
Total Citations
5
H-Index
1
About
Marzieh Yazdanzad’s research focuses on the intersection of advanced control theory and robotic systems, with a particular emphasis on exoskeleton and manipulator technologies. Her major contributions lie in the development of robust, continuous control mechanisms that ensure precise tracking performance in complex robotic applications. In her most cited work, she proposed a novel combined neural network feedforward and RISE feedback control structure for a 5-DOF upper-limb exoskeleton robot, achieving asymptotic tracking despite nonlinear disturbances and model uncertainties. This paper has garnered 4 citations, reflecting its relevance in rehabilitation and assistive robotics. Additionally, her 2014 study on the optimal design of a RISE feedback controller for a 3-DOF robot manipulator, using particle swarm optimization, demonstrated how metaheuristic algorithms can enhance control robustness—a contribution cited once but foundational for further optimization-based control studies. Yazdanzad’s work is notable for bridging theoretical control innovations with practical robotic systems, offering solutions that improve safety and accuracy in human-robot interaction. Her research is particularly valuable for students and engineers exploring robust control in medical and industrial robotics.
Research Focus
Key Achievements
Top Papers
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