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  • 标题:IFT-LPV: Data-Based Tuning of Fixed Structure Controllers for LPV Systems
  • 本地全文:下载
  • 作者:Sachin T. Navalkar ; Tom Oomen ; Jan-Willem van Wingerden
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:28
  • 页码:721-726
  • DOI:10.1016/j.ifacol.2015.12.215
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractFixed structure controllers are widely used, however the tuning thereof can be cumbersome and gives no guarantee of optimality, especially when the system is Linear Parameter-Varying (LPV). Iterative Feedback Tuning (IFT) is a technique for the optimisation of a parameterised controller based on closed-loop experiments. This paper extends the applicability of IFT to LPV systems for the case where the LPV scheduling parameters are measurable but cannot be controlled. The closed-loop LPV system matrices are factorised such that the effect of the scheduling parameter on the IFT gradient estimates can be compensated. A suffcient number of IFT experiments are performed to estimate the cost gradient and tune the parameters. The method is validated successfully via a simulation study for a special case with an LPV system.
  • 关键词:KeywordsData-based controller tuningAdaptive ControlIterative Feedback TuningLPV systemsFixed structure control design
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