contributor author | Lyu, Bensheng;Jia, Li;Li, Feng;Zhou, Chengyu | |
date accessioned | 2023-04-06T13:04:12Z | |
date available | 2023-04-06T13:04:12Z | |
date copyright | 9/27/2022 12:00:00 AM | |
date issued | 2022 | |
identifier issn | 220434 | |
identifier other | ds_144_12_121001.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4289018 | |
description abstract | The multivariable Hammerstein controlled autoregressive moving average (CARMA) system contains the sum of bilinear parameter vectors in the identification model, which is difficult to be transformed into a regression form for direct identification. A twostage identification technique is developed in this article. By using multiple sets of special test signals, this chapter achieves separable identification for the linear subsystem and the nonlinear subsystem. Then, using the property of binary signal input to nonlinear part, parameters of noise model and the linear subsystem can be calculated by recursive extended least squares (RELS) method. To implement the offline identification, the RELS is used to identify the nonlinear subsystem parameters. Finally, simulation examples illustrate the validity of proposed approach in identifying multivariable Hammerstein CARMA system. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Identification of Multivariable Hammerstein CARMA System Using Special Test Signals | |
type | Journal Paper | |
journal volume | 144 | |
journal issue | 12 | |
journal title | Journal of Dynamic Systems, Measurement, and Control | |
identifier doi | 10.1115/1.4055587 | |
journal fristpage | 121001 | |
journal lastpage | 12100111 | |
page | 11 | |
tree | Journal of Dynamic Systems, Measurement, and Control:;2022:;volume( 144 ):;issue: 012 | |
contenttype | Fulltext | |