Application of MHE to large-scale nonlinear processes with delayed lab measurements

The paper addresses nonlinear estimation problems on nonlinear processes containing several lab measurements sampled slowly and with long delay, which is the usual case in industrial polymerization applications. A moving horizon estimation algorithm is developed to compute the theoretical optimal so...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Computers & chemical engineering Ročník 80; s. 63 - 72
Hlavní autoři: Ji, Luo, Rawlings, James B.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 02.09.2015
Témata:
Algorithms
Chemical engineering
Computer simulation
Delay
Mathematical models
Moving horizon estimation
Multi-rate sampling measurements
Nonlinear state estimation
Nonlinearity
Observability
Optimization
Polymer process
Polymerization
Polymer process
Nonlinear state estimation
Observability
Moving horizon estimation
Multi-rate sampling measurements
ISSN:0098-1354, 1873-4375
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The paper addresses nonlinear estimation problems on nonlinear processes containing several lab measurements sampled slowly and with long delay, which is the usual case in industrial polymerization applications. A moving horizon estimation algorithm is developed to compute the theoretical optimal solution given the multi-rate measurements. In this algorithm, the MHE window is recalculated as the new lab measurement becomes available. Simulation studies on a polymerization process with plant model mismatch are performed. Observability analysis and estimation results of MHE with and without lab measurements show that lab measurements help identify the disturbances and can improve the performance of both estimation and closed-loop control.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2015.04.015