A Spatial Learning-based Fault Tolerant Lateral Tracking Control for Autonomous Driving

In this paper, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical uncertainties, external disturbances as well as actuator failures. In order to facilitate the controller design, the uncertain vehicle dynamics...

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Vydáno v:IEEE transactions on vehicular technology Ročník 72; číslo 10; s. 1 - 13
Hlavní autoři: Li, Xuefang, Li, Hongbo, Meng, Deyuan
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.10.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Actuator failure
Actuators
Adaptation models
Adaptive control
Algorithms
Autonomous vehicles
Control algorithms
Control systems design
Control theory
Controllers
Convergence
Fault tolerance
fault tolerant
Feasibility studies
lateral tracking
Space vehicles
Spatial adaptive iterative learning control
Tracking control
Uncertainty
Vehicle dynamics
ISSN:0018-9545, 1939-9359
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Shrnutí:In this paper, a spatial learning-based fault-tolerant control strategy is proposed for precise lateral tracking of autonomous vehicles subject to dynamical uncertainties, external disturbances as well as actuator failures. In order to facilitate the controller design, the uncertain vehicle dynamics are firstly transformed into a parametric form in the space domain, where the system uncertainties are reorganized and combined into the parametric and input distribution uncertainties. Furthermore, considering the under-actuated property of the vehicle dynamics, a novel technique in dealing with the non-square input distribution matrix is employed, in which a pseudo-like inverse matrix and a robust term are introduced into the controller to compensate the mismatch between the number of inputs and outputs. Then the proposed spatial learning-based fault tolerant control algorithm is developed, which is equipped with two adaptive parametric updating laws to estimate the parametric uncertainties and the multiplicative actuator faults correspondingly. Consequently, the convergence of the control algorithm is analyzed rigorously under the framework of composite energy function. Case studies verify the feasibility and effectiveness of the proposed control scheme.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2023.3274672