Papers

3

Total Citations

14

H-Index

2

About

Tzu-Yuan Huang is a rising researcher in the field of control systems, with a focus on safety-critical control for unknown dynamic systems. His key research areas include prescribed-time safety, control barrier functions, and system identification for robotic manipulators. Huang’s major contribution lies in developing learning-based frameworks that guarantee state constraint satisfaction within a prescribed time—even when system dynamics are unknown. His 2024 paper on “Learning-Based Prescribed-Time Safety for Control of Unknown Systems With Control Barrier Functions” (7 citations) addresses a critical gap by extending prescribed-time safety guarantees to systems with unknown dynamics. He further advanced this work in 2025 with a Gaussian Process-based approach to input-to-state safety. Additionally, Huang has made notable contributions to robotics, proposing a rapid recurrent neural network-based algorithm for testing the physical feasibility of base parameters during robot dynamic model identification (6 citations). His work bridges theoretical safety guarantees with practical implementation challenges, making him a promising voice in modern control theory and robotics.

Research Focus

Key Achievements

2
H-Index
3
Papers
14
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Learning-Based Prescribed-Time Safety for Control of Unknown Systems With Control Barrier Functions
7 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Technical University of Munich, National Cheng Kung University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago