文章基本信息

标题：Collaborative Eco-Drive of Railway Vehicles via Switched Nonlinear Model Predictive Control ⁎
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作者：Hafsa Farooqi ; Gian Paolo Incremona ; Patrizio Colaneri 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：30
页码：626-631
DOI：10.1016/j.ifacol.2018.11.225
语种：English
出版社：Elsevier
摘要：AbstractA switched Nonlinear Model Predictive Control (NMPC) strategy for time efficient energy control of railway vehicles, while fulfilling constraints on velocity, journey time and driving style in a collaborative fashion (collaborative eco-drive) is proposed. More specifically, the train dynamics are modeled as discrete, switched and nonlinear, while the optimization variable is the handle position which modulates the available traction/braking force and has to belong to a set of discrete values and/or operating modes, which the human driver is able to implement. Hence the aim is to choose the optimal handle position that minimizes the cost, is implementable by the driver and also fulfills the eco-driving objective, such that the driving style is constrained by predefined driving sequences. A supervisor detects the states of the trains and subsequently modifies the weights of the cost by negotiating between constraint satisfaction and control aggressiveness, in order to share the available regenerated braking energy among the connected trains in a substation network. The efficiency of the proposed switched NMPC strategy is demonstrated using realistic simulation case study.
关键词：KeywordsTrain controlpredictive controlnonlinear control systemsswitching algorithms