Yuqian Lin
Papers
2
Total Citations
12
H-Index
2
About
Yuqian Lin is a researcher specializing in advanced control systems, with a particular focus on fuzzy Markovian jump systems, stochastic dynamics, and sampled-data control. Their work addresses critical challenges in designing robust, asynchronous controllers for complex systems that experience random abrupt changes in structure—a common issue in networked and industrial automation. Lin’s major contributions include developing novel H∞ dynamic output feedback controllers for fuzzy Markovian jump systems, ensuring stability and performance even when system modes are not perfectly synchronized. Their 2022 paper on sampled-data H∞ control, with 7 citations, introduced a framework that bridges continuous-time and discrete-time analysis, while their subsequent work on delayed fuzzy stochastic systems, cited 5 times, advanced the use of hidden Markov model strategies to handle asynchronous control effectively. These achievements have practical implications for reliable control in uncertain environments, such as power grids and robotic systems. Lin’s research is notable for its rigorous mathematical treatment and its ability to integrate multiple challenging factors—delays, stochastic jumps, and asynchronous feedback—into unified, implementable solutions.
Research Focus
Key Achievements
Top Papers
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