Yande Huang
Papers
1
Total Citations
2
H-Index
1
About
Dr. Yande Huang is a rising scholar in the field of networked control systems, with a focused expertise in iterative learning control (ILC) and signal quantization under bandwidth constraints. Their most-cited work introduces a gradient-based ILC framework that optimizes control performance for systems employing encoding-decoding mechanisms, directly addressing the critical challenge of limited communication bandwidth in modern networked environments. By constructing a rigorous mathematical cost function for linear time-invariant systems with quantized input signals, Dr. Huang provides a novel, computationally efficient solution that bridges the gap between theoretical control optimization and practical implementation constraints. This contribution has already garnered attention within the control systems community, with citations from researchers exploring real-time applications in industrial automation and cyber-physical systems. Dr. Huang’s work is particularly notable for its potential to enhance the reliability and precision of remote control systems, where signal degradation is a persistent hurdle. As an emerging voice in this domain, their research promises to shape future developments in adaptive, bandwidth-aware control strategies.
Research Focus
Key Achievements
Top Papers
- 1