Mingwei Liang

South China University of Technology

Papers

2

Total Citations

6

H-Index

2

About

Mingwei Liang is an emerging researcher specializing in smart materials, intelligent control systems, and robotic actuation technologies. His work centers on harnessing the unique properties of shape memory alloys (SMAs) — a class of smart materials capable of generating deformation and recovery tension through thermally-induced phase transitions — to advance the design and control of sophisticated robotic systems. Liang's research addresses one of the most persistent challenges in SMA-based robotics: the nonlinear hysteresis behavior that compromises control accuracy and system performance. In his 2020 work, he developed a modified rate-dependent Prandtl-Ishlinskii hysteresis model to more precisely characterize SMA actuator dynamics, contributing a valuable tool for engineers designing minimally invasive surgical robots, micro in-pipe robots, and biomimetic systems. Building on this foundation, his 2022 study introduced a sliding mode control strategy augmented with RBF neural networks for tracking control of an SMA artificial wrist joint, demonstrating practical applications in flexible actuation for micro robots and aerospace systems. Though early in his citation trajectory — with approximately 3 citations per paper — Liang's contributions lay important groundwork in precision control methodologies for next-generation smart material actuators, positioning him as a promising voice in the robotics and intelligent materials community.

Research Focus

Key Achievements

2
H-Index
2
Papers
6
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Tracking Control of Shape Memory Alloy Artificial Wrist Joint Using Sliding Mode Control Strategy Based on RBF Neural Network
3 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: South China University of Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago