Neural networks predictive control using an adaptive control rate

Author

Mnasser, Ahmed ; Bouani, Faouzi ; Ksouri, Moufida

Author_Institution

Conception & Control of Syst. Lab., Tunis El Manar Univ., Tunis, Tunisia

fYear

2013

fDate

6-8 May 2013

Firstpage

549

Lastpage

554

Abstract

This paper deals with the predictive control of discrete time nonlinear systems based on artificial neural networks. The system behavior is described by a neural networks model and the control law is obtained by minimizing a quadratic cost function. An adaptive variable control rate which is based on Lyapunov function candidate and assumes the closed loop stability is developed. A simulation example is given in order to illustrate the performances of the proposed approach.

Keywords

Lyapunov methods; adaptive control; closed loop systems; discrete time systems; neurocontrollers; nonlinear control systems; predictive control; stability; Lyapunov function candidate; adaptive control rate; adaptive variable control rate; artificial neural networks; closed loop stability; control law; discrete time nonlinear systems; neural networks model; neural networks predictive control; quadratic cost function; system behavior; Artificial neural networks; Asymptotic stability; Neurons; Nonlinear systems; Predictive models; Stability analysis; neural networks; nonlinear systems; stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Decision and Information Technologies (CoDIT), 2013 International Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4673-5547-6

Type

conf

DOI

10.1109/CoDIT.2013.6689603

Filename

6689603