Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research

This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial...

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Detaylı Bibliyografya
Yazar: Shang, Chao (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Singapore : Springer Nature Singapore : 2018.
Imprint: Springer,
Edisyon:1st ed. 2018.
Seri Bilgileri:Springer Theses, Recognizing Outstanding Ph.D. Research,
Konular:
Security systems.
Manufactures.
Control engineering.
Statistics .
Security Science and Technology.
Machines, Tools, Processes.
Control and Systems Theory.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Online Erişim:Full-text access
İçindekiler:
  • Introduction
  • Concurrent monitoring of steady state and process dynamics with SFA
  • Online monitoring and diagnosis of control performance with SFA and contribution plots
  • Recursive SFA algorithm and adaptive monitoring system design
  • Probabilistic SFR model and its applications in dynamic quality prediction
  • Improved DPLS model with temporal smoothness and its applications in dynamic quality prediction
  • Nonlinear and dynamic soft sensing model based on Bayesian framework
  • Summary and open problems.

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