Jinxian Wu
Papers
1
Total Citations
1
H-Index
1
About
Dr. Jinxian Wu is making impactful contributions at the intersection of control theory and real-time optimization, with a primary focus on advancing model predictive control (MPC) for complex affine systems. Their most-cited work, "Convex MPC With Unreachable Setpoint for a Class of Affine System" (2025), introduces a novel convex MPC framework that strategically reduces reliance on terminal components, thereby significantly enhancing real-time control performance. By incorporating artificial reference variables, Dr. Wu elegantly addresses the challenge of unreachable setpoints, ensuring system stability even under demanding constraints. This innovation holds promise for applications in robotics, autonomous systems, and industrial automation where rapid, reliable control is critical. With growing recognition in the control community, Dr. Wu’s research bridges theoretical rigor and practical deployability, offering a streamlined yet robust approach to constrained control problems. Their work continues to inspire new directions in efficient, real-time control design.
Research Focus
Key Achievements
Top Papers
- 1Convex MPC With Unreachable Setpoint for a Class of Affine System1 citations · 2025