Mingli Zhang
Papers
1
Total Citations
16
H-Index
1
About
Mingli Zhang is a researcher whose work centers on intelligent control systems, neural network applications, and robotics—particularly in the domain of legged locomotion. Their most notable contribution is the development of an adaptive PID control method using a double-layer back propagation (BP) neural network, designed to overcome the limitations of manual parameter tuning in hydraulic drive units for legged robots. This innovation, detailed in their highly cited 2021 paper (16 citations), introduces a hierarchical learning architecture where the first layer optimizes control parameters in real time, significantly enhancing the stability and adaptability of robotic movement. Zhang’s work bridges the gap between classical control theory and modern machine learning, offering a practical solution for complex, dynamic environments. With growing recognition in the field of robotics and intelligent control, Zhang’s research continues to influence the design of more autonomous and responsive robotic systems. Their contributions are particularly valuable for students and engineers seeking to integrate neural networks with traditional control strategies for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1