Open AccessModel Error Analysis of Load Simulator System
Author(s) -
Yongjun Zheng,
Zhi Yu,
Qing Guo
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1676/1/012216
Subject(s) - simulation , computer science , nonlinear system , controller (irrigation) , artificial neural network , black box , control theory (sociology) , control (management) , artificial intelligence , physics , quantum mechanics , agronomy , biology
The load simulator is the main semi-physical simulation equipment to detect the performance of the steering gear. Linear models or black box models are often used in load simulator modeling, but the modeling error needs to be further analyzed due to its prominent nonlinear and strong coupling characteristics. In this paper, the semi-physical simulation platform of the electric load simulator was built, and a linear model and a system identification model based on Artificial Neural Network (ANN) were established respectively. The error characteristics of the above models were further analyzed by statistical distribution and power spectral density. The research results can provide support for the controller design and the selection of state estimation method.