Marjan Mirshekari
Papers
2
Total Citations
22
H-Index
2
About
Marjan Mirshekari is a researcher in nonlinear control systems and robotics, whose work focuses on advancing intelligent control strategies for complex mechanical systems. Her primary research areas include fuzzy logic control, computed torque control, and PID-based nonlinear controllers, with a particular emphasis on continuum robot manipulators. Mirshekari’s major contributions lie in the development of minimum rule-base fuzzy inference controllers that combine classical computed torque methods with adaptive fuzzy tuning, enabling robust trajectory tracking for second-order nonlinear systems. Her 2014 paper on designing a minimum rule-base fuzzy nonlinear controller has garnered 13 citations, while her subsequent work on PID baseline fuzzy tuning of proportional-derivative coefficients for continuum robots has received 9 citations. These studies demonstrate her ability to mathematically prove closed-loop stability using Lyapunov methods, a critical achievement for ensuring reliable performance in real-world robotic applications. Mirshekari’s research bridges the gap between classical control theory and modern intelligent systems, offering computationally efficient solutions for optimizing continuum robot manipulators to meet demanding trajectory requirements. Her work is particularly valuable for students and researchers exploring robust control in soft robotics and nonlinear dynamics.
Research Focus
Key Achievements
Top Papers
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