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  • 标题:Model Predictive Control of engine intake manifold pressure with an uncertain model ⁎
  • 本地全文:下载
  • 作者:Evgeny Shulga ; Patrick Lanusse ; Tudor-Bogdan Airimitoaie
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:6
  • 页码:335-340
  • DOI:10.1016/j.ifacol.2021.08.566
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper proposes a Model Predictive Control (MPC) design method for the intake manifold pressure of an internal combustion engine. This controller uses a nominal nonlinear model of the physical system to optimize a cost function. The noise sensibility of MPC is reduced and the robustness of the state estimation is achieved by using an Extended Kalman Filter (EKF). The proposed approach is evaluated using the Matlab Simulink model of the intake manifold of a spark ignition combustion engine in which parametric uncertainties and saturation are added. Different settings for EKF and MPC are tested for comparison purposes.
  • 关键词:Keywordsmodel predictive controlextended Kalman filtercombustion engineair pathrobustness
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