Minan Tang
Papers
9
Total Citations
67
H-Index
6
About
Minan Tang is a rising authority in intelligent robotic control, specializing in model predictive control (MPC), trajectory tracking, and dynamic parameter identification for collaborative and mobile robots. Their work bridges theoretical control algorithms with real-world applications, particularly in rehabilitation, emergency response, and renewable energy. Tang’s most cited paper, “Dynamic Parameter Identification of Collaborative Robot Based on WLS-RWPSO Algorithm” (2023, 18 citations), provides foundational methods for motion state control and fault diagnosis. Their 2024 study on “Trajectory tracking control of wearable upper limb rehabilitation robot based on Laguerre model predictive control” (15 citations) advances assistive robotics for healthcare. Tang has also pioneered trajectory tracking for emergency supplies transportation robots using Koopman operator theory and event-triggered MPC (7 citations), and developed motion/force coordinated control for nonholonomic wheeled mobile robots (6 citations). With additional work on photovoltaic cleaning robotic arms and fuzzy MPC, Tang’s research directly addresses critical challenges in automation, disaster logistics, and sustainable energy. Their growing citation record and diverse applications demonstrate significant impact in both theoretical and applied robotics.
Research Focus
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