Zhongqi Sun
Papers
20
Total Citations
920
H-Index
14
About
Zhongqi Sun is a prominent control systems researcher whose work centers on model predictive control (MPC), disturbance rejection, and autonomous mobile robotics. His research has made substantial contributions to solving one of the field's most persistent challenges: achieving robust, real-time trajectory tracking for nonholonomic systems—such as wheeled mobile robots and unicycle-type vehicles—under practical constraints and external disturbances. Sun's most influential contributions include pioneering disturbance rejection MPC frameworks that integrate disturbance observers to estimate and compensate for unknown or harmonic disturbances, earning over 149 and 159 citations respectively. He advanced the field further by developing event-based and self-triggered MPC schemes that significantly reduce computational burden without sacrificing tracking performance, with his 2017 event-based work accumulating 147 citations. His introduction of adaptive prediction horizons and virtual structure methods demonstrates a consistent drive toward practical, implementable solutions. Beyond mobile robotics, Sun has extended his expertise to robot manipulators, developing composite trajectory tracking controllers with prescribed performance and active disturbance rejection. With multiple papers exceeding 100 citations and a growing body of work bridging theoretical rigor with engineering applicability, Zhongqi Sun has established himself as a leading voice in intelligent control systems for autonomous robots.
Research Focus
Key Achievements
Top Papers
- 1Robust MPC for tracking constrained unicycle robots with additive disturbances159 citations · 2018
- 2Disturbance Rejection MPC for Tracking of Wheeled Mobile Robot149 citations · 2017
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