Jing-Quan Peng
Papers
1
Total Citations
7
H-Index
1
About
Jing-Quan Peng is a robotics and control systems researcher whose work focuses on adaptive control strategies for precision robotic manipulators. His primary research areas include nonlinear control theory, backstepping design, and the dynamic control of parallel kinematic machines, particularly linear delta robots. Peng’s most cited paper, "Adaptive Control of a Linear Delta Robot Based on Backstepping Design" (2018, 7 citations), makes a significant contribution by developing a second-order adaptive controller that ensures tracking errors converge to zero for both step and continuous signals, such as sine waves. This work addresses critical challenges in compensating for system nonlinearities and uncertainties, offering a robust solution for high-speed, high-accuracy automation tasks. By demonstrating that both first- and second-order controllers can achieve error convergence, Peng provides a foundational framework for improving the performance of delta robots in industrial applications like pick-and-place operations. His research bridges theoretical control design with practical robotic implementation, making it valuable for students and engineers working on advanced motion control systems.
Research Focus
Key Achievements
Top Papers
- 1Adaptive Control of a Linear Delta Robot Based on Backstepping Design7 citations · 2018