Papers
20
Total Citations
491
H-Index
11
About
Prerna Gaur is a control systems and robotics researcher whose work has made significant contributions to intelligent control design for robotic systems. Her research primarily focuses on fractional order control, fuzzy logic systems, and advanced PID architectures applied to robotic manipulators and mobile robots. Gaur's most influential contribution, a 2015 study on two-degree-of-freedom fractional order PID controllers for robotic manipulators with payload variations, has garnered over 143 citations, establishing her as a notable voice in adaptive control for nonlinear robotic systems. She has consistently pushed the boundaries of hybrid control strategies, combining fractional calculus with fuzzy logic and neural networks to tackle the inherent complexity of coupled, dynamic robotic systems. Her 2019 work on switching-based collaborative fractional order fuzzy logic controllers further demonstrates her commitment to practical, robust solutions for real-world manipulation challenges. Beyond manipulators, Gaur has extended her expertise to wheeled mobile robots, exploring nature-inspired optimization algorithms and ANFIS-based speed control. Her 2019 contribution on tremor estimation in robot-assisted surgery using Lie groups and Extended Kalman Filters reflects a meaningful pivot toward medical robotics, broadening the humanitarian impact of her research portfolio.
Research Focus
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