Hierarchical Newton and least squares iterative estimation algorithm for dynamic systems by transfer functions based on the impulse responses
L Xu, F Ding, Q Zhu - International Journal of Systems Science, 2019 - Taylor & Francis
This paper develops a parameter estimation algorithm for linear continuous-time systems
based on the hierarchical principle and the parameter decomposition strategy. Although the …
based on the hierarchical principle and the parameter decomposition strategy. Although the …
Parameter estimation algorithms for Hammerstein output error systems using Levenberg–Marquardt optimization method with varying interval measurements
J Li, WX Zheng, J Gu, L Hua - Journal of the Franklin Institute, 2017 - Elsevier
This paper studies the parameter estimation problem of Hammerstein output error
autoregressive (OEAR) systems. According to the maximum likelihood principle and the …
autoregressive (OEAR) systems. According to the maximum likelihood principle and the …
Identification of continuous-time systems with irregular samplings by invariant-subspace based method
C Huang - IEEE Transactions on Automatic Control, 2023 - ieeexplore.ieee.org
The invariant-subspace based (ISP) system identification method is developed when the
excitation signal is periodic and the measured data are obtained from irregular samplings …
excitation signal is periodic and the measured data are obtained from irregular samplings …
Issues in separable identification of continuous-time models with time-delay
This paper discusses several issues related to the identification of time-delayed continuous-
time systems using the refined instrumental variable method. The proposed estimation …
time systems using the refined instrumental variable method. The proposed estimation …
A novel recursive learning estimation algorithm of Wiener systems with quantized observations
L Li, F Wang, H Zhang, X Ren - ISA transactions, 2021 - Elsevier
In this paper, a novel recursive learning identification approach is proposed to estimate the
parameters of the Wiener systems with quantized output. By using a filter with adaptive …
parameters of the Wiener systems with quantized output. By using a filter with adaptive …
Recursive IV identification of continuous-time models with time delay from sampled data
This brief investigates recursive instrumental variable (IV) identification of time-delayed
continuous-time (CT) models from the sampled input-output data. The refined IV method is …
continuous-time (CT) models from the sampled input-output data. The refined IV method is …
Recursive least squares and multi-innovation gradient estimation algorithms for bilinear stochastic systems
D Meng - Circuits, Systems, and Signal Processing, 2017 - Springer
Bilinear systems are a special class of nonlinear systems. Some systems can be described
by using bilinear models. This paper considers the parameter identification problems of …
by using bilinear models. This paper considers the parameter identification problems of …
Design of a multivariable GPC based on an industrial PC for control of a reverse osmosis unit of a pharmaceutical industry
R Rivas-Perez, J Sotomayor-Moriano… - Revista mexicana de …, 2016 - scielo.org.mx
Resumen RIVAS-PEREZ, R.; SOTOMAYOR-MORIANO, J.; PEREZ-ZUNIGA, CG y
CALDERON-MENDOZA, EM. Design of a multivariable GPC based on an industrial PC for …
CALDERON-MENDOZA, EM. Design of a multivariable GPC based on an industrial PC for …
The bouncing ball and the Grünwald-Letnikov definition of fractional derivative
JA Tenreiro Machado - Fractional Calculus and Applied Analysis, 2021 - degruyter.com
This paper proposes a conceptual experiment embedding the model of a bouncing ball and
the Grünwald-Letnikov (GL) formulation for derivative of fractional order. The impacts of the …
the Grünwald-Letnikov (GL) formulation for derivative of fractional order. The impacts of the …
[HTML][HTML] Parameter estimation of the systems with irregularly missing data by using sequentially parallel distributed adaptive signal processing architecture
This paper considers problems related to output error models for output data estimation and
parameter identification in missing output data systems. In this regard, a new sequentially …
parameter identification in missing output data systems. In this regard, a new sequentially …