Targeting using global models built from nonstationary data

L.Y. Cao, Kevin Judd, A.I. Mees

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

We show how to perform targeting control using global models derived from data coming from possibly nonstationary dynamical systems where the varying parameters are known along with the System observations. We first identify a global model from the observations and the values of the accessible parameters. To carry out the control, we successively apply the usual targeting algorithm to the model system to get a perturbation of the accessible parameters for a given starting point and targeting point, then apply this perturbation to the true system to generate a new starting point. Because our model is approximate, we repeat the targeting and perturbation steps until the observed trajectory is near the target point. (C) 1997 Elsevier Science B.V.
Original languageEnglish
Pages (from-to)367-372
JournalPhysics Letters A
Volume231
DOIs
Publication statusPublished - 1997

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