Pariwat Imura
Papers
3
Total Citations
32
H-Index
2
About
Pariwat Imura is a rising researcher in intelligent control systems and robotics, with a focus on fuzzy logic control and sensor fusion. His work centers on optimizing the performance of autonomous and assistive robotic systems through advanced computational techniques. Imura’s most cited paper, “Optimizing Membership Function Tuning for Fuzzy Control of Robotic Manipulators Using PID-Driven Data Techniques” (2023, 26 citations), introduces a data-driven approach to automate the design of fuzzy membership functions, reducing reliance on expert intuition and significantly improving manipulator precision. He further advances the field with a comparative study of Takagi-Sugeno-Kang and Mamdani algorithms in Type-1 and Interval Type-2 fuzzy controllers for self-balancing wheelchairs (2023, 4 citations), demonstrating how interval type-2 fuzzy logic can enhance stability under uncertainty. In his 2024 work on sensor fusion, Imura compares Kalman and complementary filters for angle estimation using IMU6050 data, offering practical insights for robotics and biomedical applications. By bridging theoretical fuzzy control with real-world robotic challenges, Imura is establishing himself as a contributor to safer, more adaptive autonomous systems.
Research Focus
Key Achievements
Top Papers
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