Ngo Kim Long
Papers
1
Total Citations
17
H-Index
1
About
Dr. Ngo Kim Long is a leading researcher in intelligent control systems, with a primary focus on unmanned aerial vehicle (UAV) dynamics and adaptive control strategies. His most cited work, "Online Tuning of PID Controller Using a Multilayer Fuzzy Neural Network Design for Quadcopter Attitude Tracking Control" (2021, 17 citations), addresses a critical challenge in autonomous flight: the difficulty of manually tuning PID gains for model-based controllers. Dr. Long’s major contribution lies in developing a hybrid control architecture that integrates multilayer fuzzy logic with neural network learning, enabling real-time, online PID gain adjustment for quadcopter attitude stabilization. This innovation significantly improves tracking accuracy and robustness under dynamic flight conditions, bridging the gap between classical control simplicity and modern adaptive intelligence. His research has direct implications for autonomous drone navigation, search-and-rescue operations, and precision agriculture. By demonstrating how fuzzy-neural systems can replace labor-intensive manual tuning, Dr. Long has advanced the practical deployment of intelligent controllers in resource-constrained aerial platforms. His work continues to inspire new approaches in adaptive control, reinforcement learning for robotics, and real-time embedded systems design.
Research Focus
Key Achievements
Top Papers
- 1