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  • 标题:Pomodoro: A Novel Toolkit for Dynamic (MultiObjective) Optimization, and Model Based Control and Estimation ⁎
  • 本地全文:下载
  • 作者:Satyajeet Bhonsale ; Dries Telen ; Dominique Vercammen
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:2
  • 页码:719-724
  • DOI:10.1016/j.ifacol.2018.03.122
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper presents the software package Pomodoro which includes a collection of algorithms and tools for dynamic optimization. It also introduces the framework for multiobjective problems, model predictive control and state estimation. Pomodoro is implemented in Python and utilizes CasADi as a backbone to formulate the problem. It uses orthogonal collocation technique to solve the dynamic optimization problems and efficient third-party solvers are employed to solve the resulting nonlinear programs. The design of the software and its main modules are discussed and the user-friendliness of the software is demonstrated with the help of tutorial examples for each problem class. Lastly, the advantages and limitations of this software are discussed.
  • 关键词:KeywordsOptimal ControlMulti Objective Dynamic OptimizationModel Predictive ControlStateParameter Estimation
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