文章基本信息

标题：A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles * * This research was funded by the German Federal Ministry of Education and Research (BMBF) within the Leading-Edge Cluster Intelligent Technical Systems OstWestfalenLippe (it’s OWL).
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作者：Sebastian Peitz ; Kai Schäfer ; Sina Ober-Blöbaum 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：8674-8679
DOI：10.1016/j.ifacol.2017.08.1526
语种：English
出版社：Elsevier
摘要：AbstractWe present a new algorithm for model predictive control of non-linear systems with respect to multiple, conflicting objectives. The idea is to provide a possibility to change the objective in real-time, e.g. as a reaction to changes in the environment or the system state itself. The algorithm utilises elements from various well-established concepts, namely multiobjective optimal control, economic as well as explicit model predictive control and motion planning with motion primitives. In order to realise real-time applicability, we split the computation into an online and an offline phase and we utilise symmetries in the open-loop optimal control problem to reduce the number of multiobjective optimal control problems that need to be solved in the offline phase. The results are illustrated using the example of an electric vehicle where the longitudinal dynamics are controlled with respect to the concurrent objectives arrival time and energy consumption.
关键词：KeywordsModel predictive controlExplicit model predictive controlMultiobjective optimisationMotion planningElectric vehicles