Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

2014 ◽  
Vol 22 (11-12) ◽  
pp. 1268-1273 ◽  
Author(s):  
Hongwei Wang ◽  
Tao Liu
Keyword(s):  
Singular Value Decomposition ◽  
State Space ◽  
State Space Model ◽  
Model Identification ◽  
Singular Value ◽  
Space Model ◽  
Sampled Systems ◽  
Value Decomposition

scholarly journals Kernel Function Definition Completion for Time–Domain State–Space Representations of Radiation Forces: Application to the Hankel Singular Value Decomposition

2021 ◽  
Vol 9 (7) ◽  
pp. 768
Author(s):  
Romain Lecuyer-Le Bris ◽  
Marc Le Boulluec ◽  
Jean-Frédéric Charpentier ◽  
Mohamed Benbouzid
Keyword(s):  
Singular Value Decomposition ◽  
State Space ◽  
Kernel Function ◽  
State Space Model ◽  
Hankel Matrix ◽  
Singular Value ◽  
Radiation Forces ◽  
Function Definition ◽  
Definition Of ◽  
Value Decomposition

This paper focuses on the formulation of state–space representations of radiation forces for marine structures using Hankel Singular Value Decomposition (HSVD), a method used to obtain a state–space realization from a Hankel matrix, with the classical definition of the kernel function and its new definition given in this paper. The first part shows the influence of a term commonly neglected and the resulting improvement by taking this term into account. The second part will focus on the feedthrough matrix to understand why some models have none and why some others, such as HSVD, have one. An exact definition of the kernel function will be given underlying its discontinuity and its causality. This study also shows the interest of extrapolating hydrodynamic coefficients before approaching radiation forces by a state–space model.

IDENTIFICATION OF ON-AND OFF-LINE LINEAR STATE SPACE MODELS USING SUBSPACE METHODS

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Nurul Syahirah Khalid ◽  
Norhaliza Abd. Wahab ◽  
Muhammad Iqbal Zakaria
Keyword(s):  
State Space ◽  
State Space Model ◽  
Model Identification ◽  
State Space Models ◽  
Subspace Methods ◽  
State Space System ◽  
Linear State ◽  
Value Decomposition ◽  
Error State

In this paper, subspace identification methods are proposed to analyze the differences between On-And Off-Line Linear State Space Models Using Subspace Methods. There are several ways that can estimate the order of the system. For this paper, Singular Value Decomposition (SVD) is used to estimate the order of the system. Comparing with the others methods, this method only need a limited number of input and output data for the determination of the system matrices. Two methods of the subspace algorithm are used which is N4SID (Numerical algorithm for Subspace State Space System Identification) and MOESP (Multivariable Output-Error State-Space model identification).

R-MAX Helicopter State-Space Model Identification for Hover and Forward-Flight

2006 ◽  
Vol 51 (2) ◽  
pp. 202-210 ◽  
Author(s):  
Rendy P. Cheng ◽  
Mark B. Tischler ◽  
Greg J. Schulein
Keyword(s):  
State Space ◽  
State Space Model ◽  
Model Identification ◽  
Forward Flight ◽  
Space Model
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