Framework for discrete-time model reference adaptive control of weakly nonlinear systems with HONUs

Peter M. Benes, Ivo Bukovsky, Martin Vesely, Jan Voracek, Kei Ichiji, Noriyasu Homma

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

Abstract

This paper reviews the Higher Order Nonlinear Units (HONUs) and their fundamental supervised sample-by-sample and batch learning algorithms for data-driven controller learning when only measured data are known about the plant. We recall recently introduced conjugate gradient batch learning for weakly nonlinear plant identification with HONUs and we compare its performance to classical Levenberg-Marquard (LM). Further, we recall recursive least square (RLS) adaptation and compare its performance to L-M learning both for plant approximation and controller tuning. Further, a model reference adaptive control (MRAC) strategy with efficient controller learning for linear and weakly nonlinear plants is proposed with static HONUs that avoids recurrent computations, and its potentials and limitations with respect to plant nonlinearity are discussed. Recently developed stability approach for recurrent HONUs and for closed control loops with linear plant and nonlinear (HONU) controller is recalled and discussed in connotation stability of the adaptive closed control loop.

Original languageEnglish
Title of host publicationComputational Intelligence - 9th International Joint Conference, IJCCI 2017, Revised Selected Papers
EditorsKurosh Madani, Juan Julian Merelo, Kevin Warwick, Christophe Sabourin, Kevin Warwick
PublisherSpringer Verlag
Pages239-262
Number of pages24
ISBN (Print)9783030164683
DOIs
Publication statusPublished - 2019 Jan 1
Event9th International Joint Conference on Computational Intelligence, IJCCI 2017 - Funchal, Madeira, Portugal
Duration: 2017 Nov 12017 Nov 3

Publication series

NameStudies in Computational Intelligence
Volume829
ISSN (Print)1860-949X

Other

Other9th International Joint Conference on Computational Intelligence, IJCCI 2017
CountryPortugal
CityFunchal, Madeira
Period17/11/117/11/3

Keywords

  • Conjugate gradients
  • Higher order neural units
  • Model reference adaptive control
  • Nonlinear dynamics
  • Polynomial neural networks

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Benes, P. M., Bukovsky, I., Vesely, M., Voracek, J., Ichiji, K., & Homma, N. (2019). Framework for discrete-time model reference adaptive control of weakly nonlinear systems with HONUs. In K. Madani, J. J. Merelo, K. Warwick, C. Sabourin, & K. Warwick (Eds.), Computational Intelligence - 9th International Joint Conference, IJCCI 2017, Revised Selected Papers (pp. 239-262). (Studies in Computational Intelligence; Vol. 829). Springer Verlag. https://doi.org/10.1007/978-3-030-16469-0_13