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Multi-Model Adaptive Control for CACC Applications
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DOI：10.1109/TITS.2020.2964320.png)
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Abstract
En 中文
This paper proposes a multi-model adaptive control (MMAC) algorithm based on Youla-Kucera (YK) theory to deal with heterogeneity in cooperative adaptive cruise control (CACC) systems. The main idea of MMAC is to choose the plant in a predefined set that best approximates the system dynamics, applying the corresponding predesigned controller. A set of linear plants describing different vehicle dynamics is defined. Different CACC controllers are designed depending on these linear plants. Simulation and experimental results prove how MMAC determines the closest plant in the set, choosing the CACC system able to ensure string stability.
Keywords:
Vehicle dynamics
Stability analysis
Adaptation models
Adaptive control
Uncertainty
Heuristic algorithms
Robust control
Heterogeneous string
homogeneous string
cooperative adaptive cruise control
Youla-Kucera parameterization
multi-model adaptive control
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