A globally convergent adaptive predictor

Graham C. Goodwin, Peter J. Ramadge, Peter E. Caines

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

This paper establishes global convergence for an adaptive prediction algorithm. Key features of the algorithm are (i) a priori residuals are used in the regression vector, (ii) the input signal need not be persistently exciting, (iii) only an upper bound is required on the system order, (iv) no monitoring or projection procedure is required to guarantee stability and (v) arbitrary feedback is allowed between output and input.

Original languageEnglish (US)
Pages (from-to)135-140
Number of pages6
JournalAutomatica
Volume17
Issue number1
DOIs
StatePublished - Jan 1981
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Identification
  • adaptive control
  • prediction
  • time series analysis

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