Extremum seeking nonlinear regulator with concurrent uncertainties in exosystems and control directions

  • Shimin WANG
  • , Martin GUAY*
  • , Dabo XU
  • , Denis DOCHAIN
  • *Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

This paper proposes a non-adaptive control solution framework to the practical output regulation problem (PORP) for a class of nonlinear systems with uncertain parameters, unknown control directions and uncertain exosystem dynamics. The concurrence of the unknown control directions and uncertainties in both the system dynamics and the exosystem pose a significant challenge to the problem. In light of a nonlinear internal model approach, we first convert the robust PORP into a robust non-adaptive stabilization problem for the augmented system with integral Input-to-State Stable (iISS) inverse dynamics. By employing an extremum-seeking control (ESC) approach, the construction of our solution method avoids the use of Nussbaum-type gain techniques to address the robust PORP subject to unknown control directions with time-varying coefficients. The stability of the non-adaptive output regulation design is proven via a Lie bracket averaging technique where uniform ultimate boundedness of the closed-loop signals is guaranteed. As a result, the practical output regulation problem can be solved using the proposed non-adaptive and non-Nussbaum-type framework. Moreover, both the estimation and tracking errors uniformly asymptotically converge to zero, provided that the frequency of the dither signal goes to infinity. Finally, a simulation example with unknown coefficients is provided to exemplify the validity of the proposed control solution frameworks.

Original languageEnglish
Article number112254
Number of pages10
JournalAutomatica
Volume176
Early online date19 Mar 2025
DOIs
Publication statusPublished - Jun 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 Elsevier Ltd

Funding

This work was supported in part by NSERC, Canada and in part by NSFC, China under Grant No. 62073168. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Shuzhi Sam Ge under the direction of Editor Miroslav Krstic.

Keywords

  • Approximation method
  • Extremum seeking
  • Learning-based control
  • Non-adaptive control design
  • Nonlinear systems
  • Output regulation
  • Unknown control direction

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