Creator:
Debbache, Ghania ; Bennia, Abdelhak ; Goléa, Noureddine
Contributor:
Korbicz, Józef - red. ; Uciński, Dariusz - red.
Title:
Neural network-based MRAC control of dynamic nonlinear systems
Group publication title:
Subject and Keywords:
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.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Date:
Resource Type:
Pages:
Source:
AMCS, volume 16, number 2 (2006) ; click here to follow the link