Wavelet multiresolution model based predictive control for constrained nonlinear systems

Shu Zhang, Joseph Bentsman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a wavelet multiresolution model based adaptive model predictive control strategy for control of unknown nonlinear systems subject to input and state constraints. The wavelet multiresolution analysis framework is used as the building block to approximate the unknown nonlinear system dynamics by virtue of the promising function approximation capability of wavelet networks. The parameter estimation routine employed guarantees non-increase of the prediction error vector. The identified wavelet network nominal model is then combined within nonlinear model predictive control framework to address the adaptive constrained MPC problem. The asymptotical stability of the proposed adaptive MPC technique has been proved using Lyapunov stability theorem with terminal cost and terminal constraint. An illustrative example on the choice of the stabilizing design parameters to ensure satisfaction of stability condition is provided.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4895-4900
Number of pages6
ISBN (Print)9781479932726
DOIs
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR
Period6/4/146/6/14

Keywords

  • Adaptive systems
  • Constrained control
  • Predictive control for nonlinear systems

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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