首页    期刊浏览 2025年05月01日 星期四
登录注册

文章基本信息

  • 标题:Fuzzy Aggregation Based Multiple Models Explicit Multi Parametric MPC Design for a Quadruple Tank Process
  • 本地全文:下载
  • 作者:V. Kirubakaran ; T.K. Radhakrishnan ; N. Sivakumaran
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:1
  • 页码:555-560
  • DOI:10.1016/j.ifacol.2016.03.113
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this study, design of fuzzy aggregated multi parametric model predictive controller (mpMPC) for multivariable systems is proposed. Using first principles model (FPM) of the process, a steady state map (SSM) of input output is generated. A minimum number of linearized models are obtained from the FPM in different nominal operating regions to satisfy prediction error criterion. From gap metric measure, these models are clustered by k-means algorithm, followed by cluster representatives (CR) selection and fuzzy weights (to represent each model using aggregated CR's) calculation. For a given operating point, fuzzy weights are determined by a supervisory structure. Using these weights, the estimation model and control output (from mpMPC's designed for each CR) are aggregated. A real time quadruple tank (QT) is controlled using the proposed strategy, which is implemented on an embedded platform. Performance metrics indicate a 20% improvement in prediction and 20% improvement in control under closed loop using proposed strategy.
  • 关键词:Keywordsmulti parametric MPCfuzzy aggregationk-means clusteringhardware in loopthree tanksquadruple tank
国家哲学社会科学文献中心版权所有