Autor:

Debbache, Ghania ; Bennia, Abdelhak ; Goléa, Noureddine

Współtwórca:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Tytuł:

Neural network-based MRAC control of dynamic nonlinear systems

Tytuł publikacji grupowej:

AMCS, Volume 16 (2006)

Temat i słowa kluczowe:

neural networks ; reference model ; nonlinear systems ; adaptive control ; observers ; stability ; LMI

Abstract:

This paper presents direct model reference adaptive control for a class of nonlinear systems with unknown nonlinearities. The model following conditions are assured by using adaptive neural networks as the nonlinear state feedback controller. Both full state information and observer-based schemes are investigated. ; All the signals in the closed loop are guaranteed to be bounded and the system state is proven to converge to a small neighborhood of the reference model state. It is also shown that stability conditions can be formulated as linear matrix inequalities (LMI) that can be solved using efficient software algorithms. ; The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation results are presented to show the effectiveness of the approach.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2006

Typ zasobu:

artykuł

Strony:

219-232

Źródło:

AMCS, volume 16, number 2 (2006) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego