Adaptive predictive control using multiple models, switching and tuning

Leonardo Giovanini, Andrzej Ordys, Michael Grimble

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


In this work, a new method of design adaptive controllers for SISO systems based on multiple models and switching is presented. The controller selects the model from a given set, according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a predictive control law that ensures the robust stability of the closed-loop system and achieves the best performance for the current operating point. At each sample the proposed control scheme identifies a set of linear models that best characterizes the dynamics of the current operating region. Then, it carries out an automatic reconfiguration of the controller to achieve the best possible performance whilst providing a guarantee of robust closed-loop stability. The results are illustrated by simulations a nonlinear continuous and stirred tank reactor.
Original languageEnglish
Pages (from-to)669-681
Number of pages12
JournalInternational Journal of Control, Automation and Systems
Issue number6
Publication statusPublished - 2006


  • adaptive control
  • infinite controller cover set
  • multiple models
  • multi-objective optimization
  • predictive control


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