Hybrid quasi-ARMAX modeling scheme for identification and control of nonlinear systems

Jinglu Hu, Kousuke Kumamaru, Katsuhiro Inoue

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)

Abstract

This paper proposes a hybrid quasi-ARMAX modeling and identification scheme for nonlinear systems. The idea is to incorporate a group of certain nonlinear nonparametric models (NNMs) into a linear ARMAX structure. Particular effort is made to find a better compromise to the trade-off between the model flexibility and the simplicity for estimation by using knowledge information efficiently. As the result, we obtain a model equipped with a linear ARMAX structure, flexibility and simplicity. The effectiveness and usefulness of the proposed hybrid model are examined by applying it to identification and control of nonlinear systems.

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Decision and Control
Editors Anon
Pages1413-1418
Number of pages6
Publication statusPublished - 1996 Dec 1
Externally publishedYes
EventProceedings of the 35th IEEE Conference on Decision and Control. Part 4 (of 4) - Kobe, Jpn
Duration: 1996 Dec 111996 Dec 13

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2
ISSN (Print)0191-2216

Other

OtherProceedings of the 35th IEEE Conference on Decision and Control. Part 4 (of 4)
CityKobe, Jpn
Period96/12/1196/12/13

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Hybrid quasi-ARMAX modeling scheme for identification and control of nonlinear systems'. Together they form a unique fingerprint.

  • Cite this

    Hu, J., Kumamaru, K., & Inoue, K. (1996). Hybrid quasi-ARMAX modeling scheme for identification and control of nonlinear systems. In Anon (Ed.), Proceedings of the IEEE Conference on Decision and Control (pp. 1413-1418). (Proceedings of the IEEE Conference on Decision and Control; Vol. 2).