Skip to main navigation Skip to search Skip to main content

Adaptive generic model control for a class of nonlinear time-varying processes with input time delay

D. Wang, D.H. Zhou, Y.H. Jin, S.J. Qin

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

In this article, an adaptive control approach - Adaptive Generic Model Control (AGMC) for a class of nonlinear time-varying processes with input time delay is proposed. First, a nonlinear state predictor (NSP) is introduced, which extends the conventional generic model control (GMC) to a class of nonlinear processes with input time delay. Then a class of nonlinear time-varying processes with input time delay is further considered. A modified strong tracking filter (MSTF) is adopted to estimate the time-varying parameters of the nonlinear processes, and the state estimates are then utilized to update the plant models used in the NSP and MSTF, this results in an adaptive generic model control scheme for a class of nonlinear time-varying processes with input time delay. A modified mathematical model of a three-tank-system is used for computer simulations, the results show that the proposed AGMC algorithm is satisfactory, and it has definite robustness against model/plant mismatch in the measurement noise. © 2003 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)517-531
JournalJournal of Process Control
Volume14
Issue number5
Online published4 Nov 2003
DOIs
Publication statusPublished - Aug 2004
Externally publishedYes

Research Keywords

  • Adaptive control
  • Generic model control
  • Modified strong tracking filter
  • Nonlinear processes
  • State predictor
  • Time-varying processes

Fingerprint

Dive into the research topics of 'Adaptive generic model control for a class of nonlinear time-varying processes with input time delay'. Together they form a unique fingerprint.

Cite this