Robust model order reduction technique for MIMO systems via ANN-LMI-based state residualization

Authors:
Othman M. K. Alsmadi;Zaer. S. Abo-Hammour;Adnan M. Al-Smadi
Affiliations:
Department of Electrical Engineering, University of Jordan, Amman, Jordan;Department of Mechatronics Engineering, University of Jordan, Amman, Jordan;Department of Electronics Engineering, Yarmouk University, Irbid, Jordan
Venue:
International Journal of Circuit Theory and Applications
Year:
2012

Citing 9
Cited 0

Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
Singular Perturbation Methods in Control: Analysis and Design

Singular Perturbation Methods in Control: Analysis and Design
Computation of the Canonical Decomposition by Means of a Simultaneous Generalized Schur Decomposition

SIAM Journal on Matrix Analysis and Applications
A reduction technique of large-scale RCG interconnects in the complex frequency domain: Research Articles

International Journal of Circuit Theory and Applications
Approximation of Large-Scale Dynamical Systems (Advances in Design and Control) (Advances in Design and Control)

Approximation of Large-Scale Dynamical Systems (Advances in Design and Control) (Advances in Design and Control)
Modelling the dynamics of log-domain circuits: Research Articles

International Journal of Circuit Theory and Applications
2008 Special Issue: On the study of cellular nonlinear networks via amplitude and phase dynamics

Neural Networks
Tree-based characterization of low index circuit configurations without passivity restrictions

International Journal of Circuit Theory and Applications
NHAR: A non-homogeneous Arnoldi method for fast simulation of RCL circuits with a large number of ports

International Journal of Circuit Theory and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Even though model order reduction (MOR) techniques for linear dynamical systems are developed rather properly, there are still quite a lot of issues to be considered. This paper addresses a novel MOR technique for multi-input multi-output system with dominant eigenvalue preservation, which leads to controller cost minimization. The new technique is formulated based on an artificial neural network (ANN) prediction of an upper triangular form of the system state matrix A. Using the new system state matrix along with the linear matrix inequality (LMI) optimization method, a permutation matrix is obtained which leads to the new formulation of the complete system considered for MOR. Utilizing the non-projection state residualization technique, a reduced model order is obtained. The proposed ANN-LMI-based MOR method is compared with well-known reduction techniques such as the balanced Schur decomposition, proper orthogonal decomposition (POD), and state elimination through balanced realization. Copyright © 2010 John Wiley & Sons, Ltd.