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  • 标题:Software and Hardware Code Generation for Predictive Control Using Splitting Methods
  • 本地全文:下载
  • 作者:Harsh A. Shukla ; Bulat Khusainov ; Eric C. Kerrigan
  • 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:14386-14391
  • DOI:10.1016/j.ifacol.2017.08.2025
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper presents SPLIT, a C code generation tool for Model Predictive Control (MPC) based on operator splitting methods. In contrast to existing code generation packages, SPLIT is capable of generating both software and hardware-oriented C code to allow quick prototyping of optimization algorithms on conventional CPUs and field-programmable gate arrays (FPGAs). A Matlab interface is provided for compatibility with existing commercial and open-source software packages. A numerical study compares software, hardware and heterogeneous implementations of splitting methods and investigates MPC design trade-offs. For the considered testcases the reported speedup of hardware implementations over software realizations is 3x to 11x.
  • 关键词:KeywordsModel predictiveoptimization-based controlHardware-software co-designEmbedded computer architecturesHardware-in-the-loop simulationSplitting methods
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