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  • 标题:Controlling a Grinding Mill Circuit using Constrained Model Predictive Static Programming
  • 本地全文:下载
  • 作者:Zander M. Noome ; Johan D. le Roux
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:21
  • 页码:49-54
  • DOI:10.1016/j.ifacol.2022.09.242
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractA constrained Model Predictive Static Programming (MPSP) method is implemented in simulation to a single-stage grinding mill circuit model. The results are compared to a constrained Nonlinear Model Predictive Control (NMPC) method. Both the constrained MPSP and NMPC controllers were able to track the desired output set-points without exceeding any constraints. The comparison shows that the constrained MPSP has a faster computational time than that of the NMPC controller with similar performance. Therefore, constrained MPSP shows promise as a model-based controller for large processes where computational time limits the use of NMPC.
  • 关键词:KeywordsComputational timeModel Predictive Static Programming (MPSP)Nonlinear Model Predictive Control (NMPC)grinding millindustrial processes
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