Closed-loop parametric identification for continuous-time linear systems via new algebraic techniques
M Fliess, H Sira-Ramirez - Identification of Continuous-time Models from …, 2008 - Springer
A few years ago the present authors launched a new approach to parametric identification of
linear continuous-time systems [11]. Its main features may be summarised as follows: closed …
linear continuous-time systems [11]. Its main features may be summarised as follows: closed …
[图书][B] Errors-in-variables methods in system identification
T Söderström - 2018 - books.google.com
This book presents an overview of the different errors-in-variables (EIV) methods that can be
used for system identification. Readers will explore the properties of an EIV problem. Such …
used for system identification. Readers will explore the properties of an EIV problem. Such …
The advantages of directly identifying continuous-time transfer function models in practical applications
H Garnier, PC Young - International Journal of Control, 2014 - Taylor & Francis
The direct identification and estimation of continuous-time models from sampled data is now
mature. This paper does not present any new methodology, nor does it compare the …
mature. This paper does not present any new methodology, nor does it compare the …
An optimal IV technique for identifying continuous-time transfer function model of multiple input systems
An instrumental variable method for continuous-time model identification is proposed for
multiple input single output systems where the characteristic polynomials of the transfer …
multiple input single output systems where the characteristic polynomials of the transfer …
Identification of systems with unknown inputs using indirect input measurements
ABSTRACT A common issue with many system identification problems is that the true input
to the system is unknown. This paper extends a previously presented indirect modelling …
to the system is unknown. This paper extends a previously presented indirect modelling …
Refined instrumental variable identification of continuous-time hybrid Box-Jenkins models
This chapter describes and evaluates a statistically optimal method for the identification and
estimation 3 of continuous-time (CT) hybrid Box-Jenkins (BJ) transfer function models from …
estimation 3 of continuous-time (CT) hybrid Box-Jenkins (BJ) transfer function models from …
[HTML][HTML] New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models
The errors-in-variables identification problem concerns dynamic systems in which input and
output signals are contaminated by an additive noise. Several estimation methods have …
output signals are contaminated by an additive noise. Several estimation methods have …
On instrumental variable-based methods for errors-in-variables model identification
In this paper, the problem of identifying stochastic linear discrete-time systems from noisy
input/output data is addressed. The input noise is supposed to be white, while the output …
input/output data is addressed. The input noise is supposed to be white, while the output …
Peaking-free output-feedback adaptive neural control under a nonseparation principle
High-gain observers have been extensively applied to construct output-feedback adaptive
neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under …
neural control (ANC) for a class of feedback linearizable uncertain nonlinear systems under …
Continuous-time model identification from filtered sampled data: Error analysis
XL Hu, JS Welsh - IEEE Transactions on Automatic Control, 2020 - ieeexplore.ieee.org
In this article, an upper bound is established for the estimation error of a standard least
squares (LS) algorithm used to identify a continuous-time model from filtered, sampled input …
squares (LS) algorithm used to identify a continuous-time model from filtered, sampled input …