{"title":"Analytical Optimal Control Allocation with Time-varying Secondary Objectives","authors":"M. Schwartz, Florian Mittelviefhaus, S. Hohmann","doi":"10.1109/ICCAR49639.2020.9108002","DOIUrl":null,"url":null,"abstract":"The paper at hand presents an optimal control allocation method for linear input systems under consideration of nearly arbitrary and time-varying secondary objectives, exploiting the degrees of freedom of the systems over-actuated characteristics. The distribution is solved in real-time based on the analytical solution of the optimization. Hereby, an objective function with a quadratic as well as a linear term is considered and the time-varying weighting matrices are set up to satisfy secondary objectives. The proposed procedure is applied to a four-wheel steered and four-wheel driven electric vehicle (4WS4WD EV). Thereby, the goal is to achieve energy optimal behavior as well as maximization of the tire adhesion potential simultaneously. The posed method is compared with state of the art control allocation algorithms.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAR49639.2020.9108002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The paper at hand presents an optimal control allocation method for linear input systems under consideration of nearly arbitrary and time-varying secondary objectives, exploiting the degrees of freedom of the systems over-actuated characteristics. The distribution is solved in real-time based on the analytical solution of the optimization. Hereby, an objective function with a quadratic as well as a linear term is considered and the time-varying weighting matrices are set up to satisfy secondary objectives. The proposed procedure is applied to a four-wheel steered and four-wheel driven electric vehicle (4WS4WD EV). Thereby, the goal is to achieve energy optimal behavior as well as maximization of the tire adhesion potential simultaneously. The posed method is compared with state of the art control allocation algorithms.