Minh-Tuan Nguyen

Ho Chi Minh City University of Technology and Engineering

Papers

Total Citations

H-Index

About

Minh-Tuan Nguyen is a researcher specializing in control systems, nonlinear dynamics, and intelligent automation, with a particular focus on underactuated robotic systems. His most cited work, "ANFIS-based LQR Control for Rotary Double Parallel Inverted Pendulum" (2024), addresses the complex challenge of stabilizing a Rotary Double Inverted Pendulum in Parallel Type (PRDIP)—a highly nonlinear, underactuated robot model. In this study, Nguyen integrates Linear Quadratic Regulation (LQR) with the Adaptive Neuro-Fuzzy Inference System (ANFIS), demonstrating a hybrid approach that combines classical optimal control with adaptive learning to enhance system stability and performance. This contribution is significant for advancing control strategies in robotics and mechatronics, where precise balancing and trajectory tracking are critical. With early citation impact, his work is gaining recognition among peers exploring intelligent control methods. Nguyen’s research bridges theoretical control theory and practical implementation, offering valuable insights for students and researchers working on nonlinear systems, fuzzy logic, and autonomous robotics. His innovative use of ANFIS to optimize LQR parameters marks a notable achievement in the field of underactuated robot control.