Benjamas Panomruttanarug
Papers
6
Total Citations
43
H-Index
4
About
Benjamas Panomruttanarug is a leading researcher in advanced control systems and robotic vision, whose work bridges the gap between theoretical algorithms and practical industrial automation. Her primary research areas include iterative learning control (ILC), repetitive control, and image-based robotic manipulation. Panomruttanarug’s most significant contribution is the development of intelligent control laws that dramatically improve tracking precision in repetitive tasks—such as robotic arm positioning—without requiring complex system models. Her 2020 paper on position control using repetitive control based on inverse frequency response design has garnered 15 citations, demonstrating its influence in the field. In 2023, she advanced robotic vision by introducing a ResNet18-based image segmentation method for single and dual object detection, achieving 13 citations for its practical accuracy enhancements in automation. Her innovative work on fuzzy logic-based time-varying ILC (7 citations) and dual-design ILC for robotic manipulators (4 citations) further underscores her commitment to real-world applicability. Notably, her early research on visual feedback arm robots using ILC optimization laid the groundwork for her later successes. Panomruttanarug’s research is essential reading for engineers seeking robust, implementable solutions for high-precision robotics.
Research Focus
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