Rong‐Jong Wai
Papers
22
Total Citations
1,058
H-Index
12
About
Rong-Jong Wai is a prominent researcher in intelligent control systems, robotics, and autonomous systems, whose work has profoundly advanced the fields of robot manipulator control and mobile robotics. His research is distinguished by the seamless integration of fuzzy logic, neural networks, and classical control theory — particularly sliding-mode control and backstepping methodologies — to solve complex, real-world control challenges. Wai's most celebrated contributions center on developing sophisticated adaptive control architectures for robot manipulators. His fuzzy-neural-network inherited sliding-mode control framework (2012, 190 citations) and its backstepping counterpart (2013) demonstrated how intelligent systems could achieve high-precision position tracking while maintaining robust stability, even when actuator dynamics are explicitly accounted for. His 2008 work on T-S fuzzy model-based adaptive control (158 citations) further established him as a leading voice in model-free, intelligent robot control design. Beyond manipulators, Wai made significant strides in mobile robotics, introducing the Dynamic Petri Recurrent Fuzzy Neural Network (DPRFNN) — a novel architecture applied to path-tracking and vision-based moving-target tracking for nonholonomic mobile robots. His body of work, accumulating nearly 1,000 citations, reflects sustained influence across control engineering and intelligent systems, making him an essential reference for researchers pursuing advanced robotics and adaptive control solutions.
Research Focus
Key Achievements
Top Papers
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- 4Tracking control based on neural network strategy for robot manipulator122 citations · 2003
- 5Intelligent Optimal Control of Single-Link Flexible Robot Arm94 citations · 2004
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