Papers
2
Total Citations
54
H-Index
2
About
Feng Xie is a robotics and control systems researcher whose work focuses primarily on model predictive control (MPC) applied to nonholonomic mobile robots. His research addresses some of the most challenging problems in autonomous mobile robotics, including trajectory tracking, point stabilization, and multi-robot formation coordination. Xie's most significant contribution is the development of the first-state contractive (FSC) model predictive control algorithm, introduced in his 2008 paper, which has garnered 47 citations. This work distinguished itself from existing stabilizing MPC approaches by offering a novel stability framework without relying on terminal state penalties — a meaningful theoretical advancement in constrained nonlinear control. His earlier 2007 dissertation work further explored MPC for motion coordination, contributing a robust formation controller for leader-following scenarios in multi-robot systems. His research sits at the intersection of control theory and autonomous robotics, areas of growing importance in applications ranging from warehouse automation to autonomous vehicles. By addressing core stability and coordination challenges in nonholonomic systems — robots with inherent motion constraints — Xie has contributed foundational methods that continue to inform both theoretical and applied research in mobile robotics and intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Model predictive control of nonholonomic mobile robots7 citations · 2007