Anlong Zhang
Papers
1
Total Citations
20
H-Index
1
About
Anlong Zhang is a researcher focused on advanced control systems, particularly for robotic applications. His key research areas include nonlinear model predictive control (NMPC), neural network optimization, and flexible-joint robot dynamics. Zhang’s most notable contribution is the development of a novel NMPC technique that integrates a recurrent neural network (RNN) with differential evolution optimization (DEO) for precise position control of single-link flexible-joint robots. This work, published in 2021 and garnering 20 citations, addresses the complex challenge of controlling robots with inherent flexibility, offering improved stability and performance over traditional methods. By leveraging RNNs for system modeling and DEO for real-time optimization, Zhang has advanced the field of intelligent robotics control. His research bridges the gap between computational intelligence and practical robotic systems, demonstrating significant potential for applications in manufacturing, automation, and human-robot interaction. Zhang’s work continues to influence researchers exploring adaptive and robust control strategies for flexible mechanical systems.
Research Focus
Key Achievements
Top Papers
- 1