Decoupled Parameter Estimation Methods for Hammerstein Systems by Using Filtering Technique
Author(s) -
Dongqing Wang,
Zhen Zhang,
Bingqiang Xue
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2877622
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The implementation of parameter estimation of Hammerstein systems is much difficult due to the existing parameter products from the nonlinear block and the linear block. This paper directly decomposes the parameter coupling between the nonlinear part and the linear part in a Hammerstein system by using the estimated parameter polynomial of the coupled linear part to filter the Hammerstein system, transforms the Hammerstein system into two forms, and investigates two decoupled parameter estimation methods: the one-step decoupled least squares estimation method and the two-step decoupled least squares estimation method corresponding to the two forms. Furthermore, the computational complexity is compared between the proposed two estimation algorithms. The simulation results show the effectiveness of the proposed two estimation methods with a similar estimation accuracy.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom