Papers
3
Total Citations
8
H-Index
2
About
Wei Shang is a researcher at the forefront of intelligent robotics and logistics systems, specializing in distributed control, formation coordination, and digital twin technology. His most impactful work addresses the challenge of coordinating multiple mobile robots under real-world uncertainty. In his highly cited 2023 paper, Shang introduced an **Iterative Learning Distributed Model Predictive Control (ILDMPC)** for formation control, designing a novel performance index that accounts for system coupling and uncertainty—a key advancement over traditional quadratic approaches. This work, alongside his 2021 paper on a **data-driven robust DMPC**, has garnered 7 citations, establishing a foundation for reliable multi-robot coordination. More recently, Shang has ventured into industrial digitalization with **DigiPyramid** (2025), a multiresolution Digital Twin framework that integrates Robotic Process Automation and Bayesian Networks to enhance logistics management reliability. By bridging theoretical control with practical, heterogeneous system integration, Shang’s research offers scalable solutions for autonomous fleets and smart logistics, making him a notable contributor to both control theory and applied intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3