A direct maximum likelihood optimization approach to identification of LPV time-delay systems-Reference-Cited by-同舟云学术

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A direct maximum likelihood optimization approach to identification of LPV time-delay systems

Published:2016-05 Issue:8 Volume:353 Page:1862-1881
ISSN:0016-0032
Container-title:Journal of the Franklin Institute
language:en
Short-container-title:Journal of the Franklin Institute

Author:

Yang Xianqiang,Huang Biao,Gao Huijun

Funder

Natural Sciences and Engineering Research Council (NSERC) of Canada and China Scholarship Council (CSC)

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Networks and Communications,Signal Processing,Control and Systems Engineering

Reference28 articles.

1. Real-time implementation of fault-tolerant control systems with performance optimization;Yin;IEEE Trans. Ind. Electron.,2014

2. A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process;Yin;J. Process Control,2012

3. Generalized expectation–maximization approach to LPV process identification with randomly missing output data;Yang;Chemom. Intell. Lab. Syst.,2015

4. Refined instrumental variable methods for identification of LPV Box–Jenkins models;Laurain;Automatica,2010

5. Prediction error method for identification of LPV models;Zhao;Control Eng. Pract.,2012

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