Guo Luo
Papers
1
Total Citations
1
H-Index
1
About
Dr. Guo Luo is a robotics researcher whose work focuses on intelligent control systems for space and industrial applications. His primary research areas include trajectory tracking, wavelet neural networks, and sliding mode control, with a particular emphasis on addressing the challenges of controlling robotic manipulators under periodic interference. In his most cited paper, "Trajectory Tracking of Two-Joint Space Robot using Wavelet Neural Networks and Sliding Mode Control" (2022), Dr. Luo proposed a novel hybrid control algorithm that combines the adaptive learning capabilities of wavelet neural networks with the robust disturbance rejection of sliding mode control. This approach successfully solved the complex problem of precise trajectory tracking for two-link robot manipulators operating in space environments, where periodic disturbances pose significant control difficulties. While his citation count is still growing, Dr. Luo's work represents an important step in advancing autonomous robotic systems for space exploration and industrial automation, demonstrating how neural network-based methods can enhance traditional control strategies to achieve higher accuracy and stability in challenging operational conditions.
Research Focus
Key Achievements
Top Papers
- 1