Weimin Chen
Papers
1
Total Citations
19
H-Index
1
About
Weimin Chen is a leading figure in the field of nonlinear control theory, with a primary focus on the stabilization and output-feedback control of complex, stochastic, and time-delayed systems. His most cited work, a 2017 study on neural network-based output-feedback control for stochastic high-order nonlinear time-delay systems, has garnered 19 citations and represents a significant breakthrough in the field. In this research, Chen developed a novel control scheme that dramatically relaxes the restrictive assumptions traditionally placed on delay-dependent drift and diffusion terms. By leveraging radial basis function neural networks, his approach enables robust control even under severe time-varying delays, a challenge that has long plagued practical applications. This work has direct implications for advanced robotic systems, where precise control under uncertainty is critical. Chen's contributions are characterized by their theoretical rigor and their clear pathway to real-world implementation, establishing him as a key innovator in bridging the gap between abstract control theory and tangible engineering solutions.
Research Focus
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Top Papers
- 1