Robust RHC for wheeled vehicles with bounded disturbances

Summary The robust receding horizon control (RHC) synthesis approach is developed in this paper, for the simultaneous tracking and regulation problem (STRP) of wheeled vehicles with bounded disturbances. Considering the bounded disturbances, we firstly provide a robust positively invariant (RPI) set...

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Bibliographic Details
Published in:International journal of robust and nonlinear control 2019-05, Vol.29 (7), p.2063-2081
Main Authors: Wang, Peng, Feng, Xinxi, Li, Weihua, Ping, Xubin, Yu, Wangsheng
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Control systems design
Controllers
Disturbances
Feedback control
Linear systems
Optimal control
Predictive control
Robust control
robust positively invariant (RPI) set
robust receding horizon control (RHC)
simultaneous tracking and regulation problem (STRP)
Synthesis
Tracking
tube‐based
Vehicles
wheeled vehicles
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Summary:Summary The robust receding horizon control (RHC) synthesis approach is developed in this paper, for the simultaneous tracking and regulation problem (STRP) of wheeled vehicles with bounded disturbances. Considering the bounded disturbances, we firstly provide a robust positively invariant (RPI) set and associated feedback controller for the perturbed vehicles, which contribute to the foundation of the robust RHC synthesis approach. Then, by extending the tube‐based approach introduced in the article of Mayne et al (robust model predictive control of constrained linear systems with bounded disturbances in Automatica, 2005, vol. 41) to the STRP of wheeled vehicles, we employ the designed RPI set to determine the robust tube and terminal state region, and further construct a nominal optimal control problem. The actual control input is implemented by correcting the solved nominal input with the designed feedback controller. Following the contributed properties of the developed RPI set and extended tube‐based approach, a robust RHC algorithm is finally proposed with the guarantees of recursive feasibility and robust convergence, which can also be adapted for real‐time implementation. Additionally, due to the elaborate control design, the effect of disturbances can be completely nullified to achieve better tracking performance. The effectiveness and advantage of the proposed approach are illustrated by two simulation examples.
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.4478