State estimation of two-time scale multiple models with unmeasurable premise variables. Application to biological reactors

被引：12

作者：

Nagy-Kiss, Anca Maria ^{[1
]}

Marx, Benoit ^{[1
]}

Mourot, Gilles ^{[1
]}

Schutz, Georges ^{[2
]}

Ragot, Jose ^{[1
]}

机构：

[1] Nancy Univ, Ctr Rech Automat Nancy, 2 Ave Foret Haye, F-54516 Vandoeuvre Les Nancy, France

[2] CRP Henri Tudor, LTI Unite Business & Syst Analyt, L-1855 Luxembourg, Luxembourg

来源：

49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2010年

关键词：

multiple modeling; singularly perturbed systems; unmeasurable premise variables; LMI; L-2; approach; UNKNOWN INPUTS; DESIGN; OBSERVERS; SYSTEMS;

D O I：

10.1109/CDC.2010.5718035

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper deals with the state estimation of nonlinear systems. The systems under study are characterized by two-time scale models. The state estimation is performed by designing a proportional integral observer (PIO) with unknown inputs. In order to design such an observer, the nonlinear model is transformed into an equivalent multiple model form and the fast dynamics are considered as unknown inputs. An application to an ASM1 model of Wastewater Treatment Plants (WWTP) is considered and the obtained numerical results show the performances of the proposed approach.

引用

页码：5689 / 5694

页数：6

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