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Performance Evaluation Of Nonlinear Automated Model Generation Approaches For High Level Fault Modeling

Malik, Aamir Saeed and Farooq, Muhammad Umer and Xia, Likun and Hussin, Fawnizu Azmadi (2012) Performance Evaluation Of Nonlinear Automated Model Generation Approaches For High Level Fault Modeling. In: 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), 18-20 July, Singapore.

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Abstract

It is known that automated model generation (AMG) techniques are sufficiently mature to handle linear systems. Other AMG techniques have been working reasonably well for various levels of nonlinear behavior. However, most of the modeling are performed under MATLAB environment. To be more realistic, the models need to be translated into hardware description language (HDL) models, such as VHDL-AMS or Verilog-AMS models, to perform high level modeling (HLM) and high level fault modeling (HLFM), which is a challenging task due to its nonlinear behavior. In this paper, the capability of System Identification (SI) based nonlinear AMG techniques is investigated by converting MATLAB models into VHDL-AMS models and to perform HLFM. Several faults are modeled successfully in MATLAB environment using AMG. However, they failed to perform HLFM when run in HDL simulator SystemVision.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Research Institutes > Institute for Health Analytics
ID Code:8455
Deposited By: Dr Aamir Saeed Malik
Deposited On:22 Nov 2012 02:56
Last Modified:19 Jan 2017 08:21

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