Min-Max Model Predictive Controller for Trajectory Tracking of a Wheeled Mobile Robot with Slipping Effects

2011 ◽  
Vol E94-A (2) ◽  
pp. 680-687 ◽  
Author(s):  
Yu GAO ◽  
Kil To CHONG
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Wheeled Mobile Robot ◽  
Model Predictive Controller ◽  
Predictive Controller

A hierarchical constraint approach for dynamic modeling and trajectory tracking control of a mobile robot

2021 ◽  
pp. 107754632199918
Author(s):  
Rongrong Yu ◽  
Shuhui Ding ◽  
Heqiang Tian ◽  
Ye-Hwa Chen
Keyword(s):  
Mobile Robot ◽  
Dynamic Modeling ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Wheeled Mobile Robot ◽  
Structural Constraints ◽  
Control Force ◽  
Trajectory Tracking Control ◽  
Motion Constraints ◽  
Constraint Approach

The dynamic modeling and trajectory tracking control of a mobile robot is handled by a hierarchical constraint approach in this study. When the wheeled mobile robot with complex generalized coordinates has structural constraints and motion constraints, the number of constraints is large and the properties of them are different. Therefore, it is difficult to get the dynamic model and trajectory tracking control force of the wheeled mobile robot at the same time. To solve the aforementioned problem, a creative hierarchical constraint approach based on the Udwadia–Kalaba theory is proposed. In this approach, constraints are classified into two levels, structural constraints are the first level and motion constraints are the second level. In the second level constraint, arbitrary initial conditions may cause the trajectory to diverge. Thus, we propose the asymptotic convergence criterion to deal with it. Then, the analytical dynamic equation and trajectory tracking control force of the wheeled mobile robot can be obtained simultaneously. To verify the effectiveness and accuracy of this methodology, a numerical simulation of a three-wheeled mobile robot is carried out.

Effect of Short-Term Weather Predictions on Model Predictive Trajectory Tracking Performance of Unmanned Surface Vessels

2020 ◽  
Author(s):  
Benjamin Armentor ◽  
Joseph Stevens ◽  
Nathan Madsen ◽  
Andrew Durand ◽  
Joshua Vaughan
Keyword(s):  
Trajectory Tracking ◽  
Wind Waves ◽  
Tracking Error ◽  
Tracking Performance ◽  
Model Predictive Controller ◽  
Prediction Horizon ◽  
Surface Vessels ◽  
Waves And Currents ◽  
Predictive Controller ◽  
Disturbance Model

Abstract For mobile robots, such as Autonomous Surface Vessels (ASVs), limiting error from a target trajectory is necessary for effective and safe operation. This can be difficult when subjected to environmental disturbances like wind, waves, and currents. This work compares the tracking performance of an ASV using a Model Predictive Controller that includes a model of these disturbances. Two disturbance models are compared. One prediction model assumes the current disturbance measurements are constant over the entire prediction horizon. The other uses a statistical model of the disturbances over the prediction horizon. The Model Predictive Controller performance is also compared to a PI-controlled system under the same disturbance conditions. Including a disturbance model in the prediction of the dynamics decreases the trajectory tracking error over the entire disturbance spectrum, especially for longer horizon lengths.

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