Motion control framework for unmanned wheel-legged hybrid vehicle considering uncertain disturbances based robust model predictive control

The paper proposes a motion control framework for the unmanned wheel-legged hybrid vehicle to track the motion trajectory considering uncertain disturbances. The whole-body dynamic model is built with the contact force of each rolling wheel, which serves as the foundation to obtain trajectory tracki...

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Bibliographic Details
Published in:Journal of vibration and control 2024-02, Vol.30 (3-4), p.837-849
Main Authors: Liu, Baoshuai, Liu, Hui, Han, Ziyong, Qin, Yechen, Han, Lijin, Ren, Xiaolei
Format: Article
Language:English
Subjects:
Algorithms
Angular momentum
Contact force
Control theory
Disturbances
Dynamic models
Hybrid vehicles
Motion control
Motion planning
Predictive control
Quadratic programming
Robust control
Torque
Trajectories
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Summary:The paper proposes a motion control framework for the unmanned wheel-legged hybrid vehicle to track the motion trajectory considering uncertain disturbances. The whole-body dynamic model is built with the contact force of each rolling wheel, which serves as the foundation to obtain trajectory tracking. The angular momentum and linear momentum are optimized by the robust model predictive control algorithm considering the soft constraint of the relaxation variable. The contact force between wheel and ground is solved by the quadratic programming algorithm to efficiently obtain the flexion/extension joint and wheel motion planning. Then, the explicit algorithm to calculate the torque commands of the flexion/extension joint considering the feed-forward torque and feedback torque to improve the control accuracy. Simulation results validate that the control framework based on the robust model predictive control algorithm can solve the uncertain disturbances in process of the vehicle running on the rough road.
ISSN:1077-5463
1741-2986
DOI:10.1177/10775463231151998