Convergence analysis of a combined output error-equation error algorithm

2003 ◽  
Author(s):  
J.B. Kenney ◽  
C.E. Rohrs
Keyword(s):  
Convergence Analysis ◽  
Error Equation ◽  
Output Error ◽  
Equation Error

Advances in System Identification Using Fractional Models

2008 ◽  
Vol 3 (2) ◽  
Author(s):  
Rachid Malti ◽  
Stephane Victor ◽  
Alain Oustaloup
Keyword(s):  
System Identification ◽  
Least Squares ◽  
Prior Knowledge ◽  
Time Domain ◽  
Simultaneous Estimation ◽  
Thermal System ◽  
Fractional Model ◽  
Output Error ◽  
Equation Error ◽  
Fractional Models

This paper presents an up to date advances in time-domain system identification using fractional models. Both equation-error- and output-error-based models are detailed. In the former models, prior knowledge is generally used to fix differentiation orders; model coefficients are estimated using least squares. The latter models allow simultaneous estimation of model coefficients and differentiation orders using nonlinear programing. As an example, a thermal system is identified using a fractional model and is compared to a rational one.

Equation error versus output error methods

Ergonomics ◽  
1992 ◽  
Vol 35 (5-6) ◽  
pp. 551-564 ◽  
Author(s):  
YUTAKA TOMITA ◽  
AD A. H. DAMEN ◽  
PAUL M. J. VAN DEN HOF
Keyword(s):  
Output Error ◽  
Equation Error

ON THE PARAMETERS ESTIMATION OF THE DUFFING SYSTEM BY SYSTEMS SYNCHRONIZATION

2010 ◽  
Vol 20 (10) ◽  
pp. 3303-3309 ◽  
Author(s):  
CARLOS AGUILAR-IBÁÑEZ ◽  
E. HERNÁNDEZ R ◽  
MIGUEL S. SUÁREZ-CASTAÑÓN
Keyword(s):  
Mechanical System ◽  
Convergence Analysis ◽  
Chaotic Behavior ◽  
Parameters Estimation ◽  
Control Law ◽  
Slave System ◽  
Unknown Parameters ◽  
Duffing System ◽  
Output Error ◽  
Barbalat’S Lemma

In this paper, we present a Lyapunov based approach for synchronizing, identifying the unknown parameters of the Duffing Mechanical System. The strategy consists of proposing a slave system which has to follow asymptotically a selected master Duffing system. The gains of the slave system are adjusted continuously according to a convenient adaptative control law, until the measurable output error converges to zero. The convergence analysis is carried out by using Barbalat's lemma. The parameters identification method does not always rely on the chaotic behavior of the Duffing system.

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