Adaptive control for a class of partially unknown non-affine systems: Applied to autonomous surface vessels

Ali Haseltalab, Rudy R. Negenborn

Research output: Contribution to journalConference articleScientificpeer-review

7 Citations (Scopus)

Abstract

In this paper, a neural network-based adaptive control algorithm is proposed for a class of non-affine systems where the nonlinear influence of the system input on the states is unknown. The algorithm transforms the problem of controlling non-affine systems to control of nonlinear affine systems and then, by approximating the inverse of the input function, calculates feasible control input. Lyapunov technique, Uniform Ultimate Boundedness and Matrix Singular Values are used for stability analysis and design of the controller. In order to investigate the performance of the algorithm, it is applied to an autonomous vessel where the dynamics of the propeller is unknown.

Original languageEnglish
Pages (from-to)4252-4257
JournalIFAC-PapersOnLine
Volume50
Issue number1
DOIs
Publication statusPublished - 2017
Event20th World Congress of the International Federation of Automatic Control (IFAC), 2017 - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
Conference number: 20
https://www.ifac2017.org

Keywords

  • Adaptive Control
  • Autonomous Vessels
  • Neural Networks

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