Neural Predictive Controller of Nonlinear Systems Based on Quasi-ARX Neural Network

Sutrisno, Imam and Abu Jami’in, Mohammad and Hu, Jinglu (2012) Neural Predictive Controller of Nonlinear Systems Based on Quasi-ARX Neural Network. Proceedings of the 18th International Conference on Automation & Computing, Loughborough University, Leicestershire, UK.

[img] Text
2012 ICAC.pdf - Published Version

Download (811kB)

Abstract

This paper present a neural predictive controller (NPC) based on improved quasi-ARX neural network (IQARXNN) for nonlinear dynamical systems. The IQARXNN is used as a model identifier with switching algorithm and switching stability analysis. The primary controller is designed based on a modified Elman neural network (MENN) controller using back-propagation (BP) learning algorithm with modified particle swarm optimization (MPSO) to adjust the learning rates in the BP process to improve the learning capability. The adaptive learning rates of the controller are investigated via Lyapunov stability theorem, which are respectively used to guarantee the convergences of the predictive controller. Performance of the proposed MENN controller with MPSO is verified by simulation results to show the effectiveness of the proposed method both on stability and accuracy.

Item Type: Article
Subjects: R Medicine > R Medicine (General)
T Technology > T Technology (General)
Divisions: Jurusan Teknik Kelistrikan Kapal > Teknik Kelistrikan Kapal
Depositing User: Unnamed user with email repository@ppns.ac.id
Date Deposited: 22 Jan 2019 05:52
Last Modified: 28 Jan 2019 03:14
URI: http://repository.ppns.ac.id/id/eprint/1399

Actions (login required)

View Item View Item