Mingchao Guo

About

Mingchao Guo is a leading researcher in mobile robotics, specializing in advanced control strategies for wheeled mobile robots. His work focuses on trajectory tracking and disturbance rejection, where he has pioneered the integration of model predictive control (MPC) with active disturbance rejection control (ADRC) to enhance real-time robustness and precision. Guo’s most cited paper (2017, 78 citations) introduces MPC with softening constraints to handle external disturbances, significantly improving tracking accuracy in non-holonomic systems. His subsequent study (2019, 40 citations) advances this by proposing a dual closed-loop architecture, combining ADRC’s extended state observer for disturbance estimation with MPC for optimal path following. These contributions have established a framework for resilient autonomous navigation in challenging environments, with direct applications in industrial automation and service robotics. Guo’s work is widely recognized for bridging theoretical control design and practical implementation, earning him a reputation as a key innovator in the field. His research continues to influence the development of robust, real-time control systems for mobile robots, making him a vital reference for students and engineers pursuing advancements in autonomous mobility.

Research Focus

Key Achievements

Top Papers

1. 1
   Trajectory tracking for wheeled mobile robots via model predictive control with softening constraints

   78 citations · 2017
2. 2
   Dual closed‐loop tracking control for wheeled mobile robots via active disturbance rejection control and model predictive control

   40 citations · 2019

Key Collaborators

Contact & Links