文章基本信息

标题：Network Topology Impact on the Identification of Dynamic Network Models with Application to Autonomous Vehicle Platooning ⁎
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作者：Guilherme A. Pimentel ; Rafael de Vasconcelos ; Aurélio Salton 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：1031-1036
DOI：10.1016/j.ifacol.2020.12.1284
语种：English
出版社：Elsevier
摘要：AbstractThe interconnection of complex devices in network structures has been a challenging topic in the system identification research domain. This study presents the model identification of autonomous vehicles in platoon formation, which can be cast as a dynamic network. The paper presents the comparison between two network structures: (i) a vehicle-based network, which considers the interconnection between the vehicles based only on the velocity measurements, and (ii) a sensor-based network that considers the available sensor, i.e. the velocity and the relative distance measurements. The comparison is based on the difference between the identified transfer functions and the true ones, and the analysis of the identified air resistance coefficient variances. In addition, the paper presents the identifiability requirements for both network topologies. Simulation results show that for the same data set the variance of the identified parameters can be almost five times smaller if the system is represented as a sensor-based network, but some conditions to guarantee the identifiability of this network structure must be fulfilled.
关键词：KeywordsIdentificationdynamic network modelidentifiabilitynetwork topologiesinterconnected systemsautonomous vehicles