Affiliation:
1. School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu China
2. School of Computer, Data and Mathematical Sciences Western Sydney University Sydney New South Wales Australia
Abstract
SummaryIn this article, we study parameter estimation problems for fractional commensurate Hammerstein systems utilizing the conformable fractional derivative. Two algorithms are investigated: first, the Poisson moment functions (PMF) method, aiming to transfer the fractional derivative of the measurement signal into PMF using the fractional Laplace transform and convolution; second, a proposed new instrumental variable algorithm, which is based on the conformable fractional derivative. Both algorithms have been analyzed and shown to be consistent. A comprehensive complexity analysis is provided for each algorithm. Furthermore, a kind of special time‐varying systems are discussed under the conformable fractional derivative. Finally, an example is given to illustrate the effectiveness of the proposed algorithms.
Funder
Sichuan Province Science and Technology Support Program
Reference44 articles.
1. Linear system identification based on a Kronecker product decomposition;Paleologu C;IEEE/ACM Trans Audio Speech Lang Process,2018
2. Robust EM kernel‐based methods for linear system identification;Bottegal G;Automatica,2016
3. Identification of multivariable fractional order systems;Djamah T;Asian J Control,2013
4. A new kernel‐based approach for linear system identification;Pillonetto G;Automatica,2010
5. Vector fitting fractional system identification using particle swarm optimization;Mansouri R;Appl Math Comput,2008