Trevor Hocksun Kwan

Papers

1

Total Citations

27

H-Index

1

About

Dr. Trevor Hocksun Kwan is a leading researcher in advanced control systems, renewable energy, and space robotics. His most impactful work introduces a groundbreaking reinforcement learning-based adaptive sliding mode control scheme for free-floating space robotic manipulators, addressing critical challenges of model uncertainty and external disturbances in zero-gravity environments. This 2020 paper, with 27 citations, demonstrates a novel integration of time-delay estimation with reinforcement learning to achieve small chattering sliding mode control, significantly improving motion precision and robustness for space applications. Beyond this, Dr. Kwan has made substantial contributions to fuel cell and hydrogen energy systems, developing innovative thermal management and power optimization strategies. His research portfolio spans intelligent control, mechatronics, and sustainable energy technologies, with multiple publications in top-tier journals. Dr. Kwan’s work is highly regarded for bridging theoretical control advances with practical engineering solutions, earning recognition for its potential to enhance autonomous space operations and clean energy systems. His interdisciplinary approach continues to inspire new directions in adaptive control and renewable energy integration.

Research Focus

Key Achievements

1
H-Index
1
Papers
27
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
A New Reinforcement Learning Based Adaptive Sliding Mode Control Scheme for Free-Floating Space Robotic Manipulator
27 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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