Nonlinear Model-Predictive Control Based on Quasi-ARX Radial-Basis Function-Neural-Network

Sutrisno, Imam and Abu Jami’in, Mohammad and Hu, Jinglu and Hamiruce Marhaban, Mohammad and Mariun, Norman (2014) Nonlinear Model-Predictive Control Based on Quasi-ARX Radial-Basis Function-Neural-Network. 8th Asia Modelling Symposium. ISSN 978-1-4799-6487-1

[img] Text
2014 AMS.pdf

Download (214kB)

Abstract

A nonlinear model-predictive control (NMPC) is demonstrated for nonlinear systems using an improved fuzzy switching law. The proposed moving average filter fuzzy switching law (MAFFSL) is composed of a quasi-ARX radial basis function neural network (RBFNN) prediction model and a fuzzy switching law. An adaptive controller is designed based on a NMPC. a MAFFSL is constructed based on the system switching criterion function which is better than the (ON/OFF) switching law and a RBFNN is used to replace the neural network (NN) in the quasi-ARX black box model which is understood in terms of parameters and is not an absolute black box model, in comparison with NN. The proposed controller performance is verified through numerical simulations to demonstrate the effectiveness of the proposed method.

Item Type: Article
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Jurusan Teknik Kelistrikan Kapal > Teknik Kelistrikan Kapal
Depositing User: Unnamed user with email repository@ppns.ac.id
Date Deposited: 22 Jan 2019 07:13
Last Modified: 28 Jan 2019 02:59
URI: http://repository.ppns.ac.id/id/eprint/1402

Actions (login required)

View Item View Item