Myo Min Htut
Papers
1
Total Citations
9
H-Index
1
About
Myo Min Htut’s research centers on precision motion control and industrial automation, with a particular focus on enhancing the performance of PID controllers for point-to-point (PTP) positioning systems. His most cited work, “Neural-tuned PID controller for Point-to-point (PTP) positioning system: Model reference approach” (2009, 9 citations), introduces a novel hybrid approach that integrates neural network tuning with classical PID control. This contribution addresses a critical challenge in advanced manufacturing, semiconductor fabrication, and robotics—where accurate and repeatable positioning is essential. By developing a model reference framework, Htut demonstrated how adaptive neural tuning can improve the responsiveness and robustness of PID controllers, which remain the industry standard due to their simplicity and reliability. His work bridges the gap between traditional control theory and modern intelligent systems, offering practical solutions for real-world automation. Though his citation count is modest, the targeted impact of his research is evident in its application to high-precision engineering fields. Htut’s contributions underscore the ongoing relevance of PID control in an era of increasingly complex automation demands, making his work a valuable reference for students and researchers exploring intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1