Papers
14
Total Citations
385
H-Index
11
About
Kunming Zheng is a leading researcher in intelligent robotics control, specializing in the design of advanced fuzzy neural network and backstepping control systems for complex, multi-degree-of-freedom robots. His work addresses critical challenges in high-speed, high-precision automation, particularly for industrial parallel robots like the Delta robot. Zheng’s most influential paper, “Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system” (2020), has garnered 113 citations, establishing a foundational framework for integrating fuzzy logic with neural networks to manage system nonlinearities and disturbances. He has also pioneered model-free control development and adaptive memetic differential evolution algorithms, significantly reducing computational complexity while enhancing trajectory accuracy and vibration suppression. Notably, his comprehensive analysis of position error and vibration in Delta robots (2016) and his research on intelligent vibration suppression for high-speed lightweight variants (2021) have directly improved positioning efficiency and stability in industrial settings. With over 360 total citations across his top ten works, Zheng’s contributions are widely recognized for bridging theoretical control methods with practical robotic applications, including autonomous obstacle avoidance for mobile robots. His innovative, cost-effective strategies continue to shape the future of intelligent automation and robotic system design.
Research Focus
Key Achievements
Top Papers
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- 6Trajectory planning of multi-degree-of-freedom robot with coupling effect26 citations · 2019
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