Yiran Shi
Papers
1
Total Citations
19
H-Index
1
About
Yiran Shi is a control systems researcher whose work focuses on fault-tolerant control for complex nonlinear systems, with particular applications in robotics and aeronautics. Their most-cited paper, "Fault tolerant control for nonlinear systems using sliding mode and adaptive neural network estimator" (2019, 19 citations), introduces a novel control scheme that combines sliding mode control with an adaptive neural network estimator. This approach maintains system stability even after faults occur, using a neural network to estimate uncertainties and disturbances in real time. Shi’s contributions are significant for improving the reliability and safety of autonomous and safety-critical systems. By integrating robust sliding mode techniques with adaptive neural networks, their work offers practical solutions for maintaining performance under post-fault dynamics—a key challenge in modern control engineering. With 19 citations, this paper has already gained recognition among researchers working on resilient control strategies. Shi’s research is particularly valuable for students and engineers interested in advanced fault-tolerant control, nonlinear system theory, and the intersection of machine learning with classical control methods.
Research Focus
Key Achievements
Top Papers
- 1