The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Multivariable Adaptive Control

På svenska

Author

Summary, in English

This thesis treats the problem of direct adaptive control of linear multivariable systems. The parametrization problem of adaptive control is discussed extensively. A pole-placement problem and a model-matching problem are formulated and interpreted in terms of model reference control. The problem is solved via a discussion on system invariants of multivariable systems as presented by Pernebo. The attention is then directed towards problems of identification and two different estimation schemes are formulated. Parameter convergence is guaranteed provided some conditions on /a priori/ information are satisfied. The requested prior knowledge is formulated in terms of the non-invertible system for the suggested prediction error identification algorithm. The second parameter adjustment law is shown to converge when a certain approximant of the left structure matrix, /i.e./, the system invariant is known. This result relaxes a result by Elliott /et al./ where the interactor is required to be known.

The important question of stability of adaptive systems is also treated. The major result is a method for construction of Lyapunov functions for a class of single-input systems. Stability in the sense of Lyapunov and exponential convergence are shown.

Publishing year

1983

Language

English

Publication/Series

PhD Thesis TFRT-1024

Document type

Dissertation

Publisher

Department of Automatic Control, Lund Institute of Technology (LTH)

Topic

  • Control Engineering

Status

Published

ISBN/ISSN/Other

  • ISSN: 0280-5316
  • ISSN: 0280-5316