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Multiple Model Adaptive Control

  • João M. LemosEmail author
  • Rui Neves-Silva
  • José M. Igreja
Chapter
  • 1.2k Downloads
Part of the Advances in Industrial Control book series (AIC)

Abstract

When the plant to control is subject to large variations of its point of operation, or if some of its parameters are uncertain, the corresponding change in local dynamics prevents a single linear controller to yield a good performance, or even to globally stabilize the system. In order to tackle this issue, the approach followed in the present chapter consists of the identification of a bank of linear models that represent the plant dynamics in different regions of operation and/or different parameter ranges. To each of these so called local models a linear controller (named local controller) is associated that is designed such that, when connected to the plant, it yields the desired performance in the operating region/parameter range to which the local model is associated. To prevent instability that stems from fast switching a dwell time condition is imposed, meaning that, when a local controller is connected to the plant, it remains so for at least a minimum time interval. The application of this multiple model adaptive control (MMAC) strategy is illustrated by its experimental application to an air heating fan and a distributed collector solar field.

Keywords

Local Model Static Gain Manipulate Variable Local Controller Plant Dynamic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • João M. Lemos
    • 1
    Email author
  • Rui Neves-Silva
    • 2
  • José M. Igreja
    • 3
  1. 1.INESC-ID ISTUniversity of LisbonLisboaPortugal
  2. 2.FCTNew University of LisbonCaparicaPortugal
  3. 3.Institute of Engineering of LisbonLisboaPortugal

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