Xiangjie Liu
Papers
1
Total Citations
4
H-Index
1
About
Xiangjie Liu is a leading researcher in advanced control systems, with key contributions spanning nonlinear model predictive control, iterative learning control, and fuzzy modeling for robotic and industrial applications. His most-cited work, "Nonlinear model predictive iterative learning control for robotic system" (2012), introduced a novel NMPILC framework that integrates iterative learning with model predictive control, using a fuzzy model of local linear dynamics to handle nonlinear plant behavior. This approach enables the controller to leverage historical data alongside real-time measurements, significantly improving trajectory tracking and disturbance rejection in robotic systems. With 4 citations, this foundational paper has influenced subsequent research in learning-based control for automation. Liu’s work bridges theoretical advances and practical implementation, addressing challenges in system nonlinearity and repetitive tasks. His research is particularly relevant for students and engineers working on intelligent robotics, process control, and adaptive systems, offering a robust methodology for enhancing performance in complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Nonlinear model predictive iterative learning control for robotic system4 citations · 2012