Closed-loop subspace predictive control

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientific

Abstract

This chapter considers subspace predictive control of systems whose dynamics can be described locally by LTI models. The control algorithm is based on the predictor-based subspace identification framework. In a linear least-squares problem, the observer Markov parameters of the system are recursively estimated. Those parameters are used to construct an output predictor which is in turn used to solve a predictive control problem subject to constraints.

Original languageEnglish
Title of host publicationControl-Oriented Modelling and Identification: Theory and Practice
EditorsM Lovera
Place of PublicationLondon, UK
PublisherInstitution of Engineering and Technology
Pages143-157
Volume80
ISBN (Electronic)9781849196154
ISBN (Print)9781849196147
DOIs
Publication statusPublished - 2015

Publication series

NameIET Control Engineering Series
PublisherIET
Volume80

Keywords

  • Closed loop systems
  • Closed-loop subspace predictive control
  • Invariance
  • Least squares approximations
  • Linear least-squares problem
  • LTI model
  • Markov processes
  • Observer markov parameter
  • Observers
  • Predictive control
  • Predictor-based subspace identification framework
  • Recursive estimation
  • Spc

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