Papers
1
Total Citations
7
H-Index
1
About
Ying Sun is a robotics and control systems researcher whose work focuses on the development of intelligent control algorithms for articulated robotic systems. Sun's most notable contribution lies in advancing adaptive fuzzy sliding mode control methodologies, addressing one of the longstanding challenges in conventional sliding mode control — the chattering phenomenon that limits precision and performance in robotic applications. In their 2017 paper, "Adaptive Fuzzy Sliding Mode Control Algorithm Simulation for 2-DOF Articulated Robot," Sun proposed an innovative approach that integrates adaptive single input-output fuzzy systems to dynamically compute control parameters, resulting in smoother and more robust robotic motion control. This work has garnered 7 citations, reflecting its relevance within the specialized community of robotics control engineering. By bridging fuzzy logic with sliding mode theory, Sun's research contributes meaningful solutions to real-world challenges in robotic arm manipulation, particularly for degrees-of-freedom systems commonly found in industrial and research settings. Sun's contributions offer valuable insights for engineers and researchers seeking to improve stability, adaptability, and precision in next-generation robotic control system design.
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