NDLI: Robust global identification of linear parameter varying systems with generalised expectation–maximisation algorithm

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Robust global identification of linear parameter varying systems with generalised expectation–maximisation algorithm

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The Journal of Engineering

Robust global identification of linear parameter varying systems with generalised expectation–maximisation algorithm

Content Provider	IET Digital Library
Author	Yang, Xianqiang Lu, Yaojie Yan, Zhibin
Abstract	In this study, a robust approach to global identification of linear parameter varying (LPV) systems in an input–output setting is proposed. In practice, the industrial process data are often contaminated with outliers. In order to handle outliers in process modelling, the robust LPV modelling problem is formulated and solved in the scheme of generalised expectation–maximisation (GEM) algorithm. The measurement noise is taken to follow the Student's t-distribution instead of using the conventional Gaussian distribution, in this algorithm. The extent of robustness of the proposed approach is adaptively adjusted by optimising the degrees of freedom parameter of the Student's t-distribution iteratively through the maximisation step of the GEM algorithm. The numerical example is provided to demonstrate the effectiveness of the proposed approach.
Starting Page	1103
Ending Page	1110
Page Count	8
ISSN	17518644
Volume Number	9
e-ISSN	17518652
Issue Number	Issue 7, Apr (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/9/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2014.0694
Journal	IET Control Theory & Applications
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Conventional Gaussian Distribution Degrees of Freedom Parameter Expectation-maximisation Algorithm Gaussian Distribution GEM Algorithm Generalised Expectation–maximisation Algorithm Identification Industrial Process Data Input–output Setting Linear Parameter Varying System Linear System LPV System Measurement Noise Modelling And Identification Process Modelling Robust Control Robust Global Identification Robust LPV Modelling Problem Simulation Stability in Control Theory Statistics Student T-distribution
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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