State estimation based on projection observers applied to sequential treatment based on ozonation and aerobic biodegradation: Application for phenolic wastewaters

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The adaptive linearization of dynamic nonlinear systems remains, in general, as an open problem due the complexities associated to the method required to derive the linear or quasi-linear model. The problem is even more difficult if the system is uncertain, that is, when the formal description of the plant is almost unknown considering that number of states is available. This chapter discusses an adaptive linearization method for perturbed nonlinear uncertain systems based on the application of special artificial neural networks. The proposal is based on no-parametric identifier and its convergence is analyzed using the second method of Lyapunov. The suggested structure preserves some inherited structural properties like controllability. The scheme was tested using three different set of activation functions: sigmoid, wavelets and Chevyshev polynomials. The proposed method shows a good transient performance and the identification goals are fulfilled. A distillation column was used to show how the identifier works.

Original languageEnglish
Title of host publicationBiotechnology
Subtitle of host publicationHealth, Food, Energy and Environment Applications
PublisherNova Science Publishers, Inc.
Pages43-64
Number of pages22
ISBN (Print)9781620810712
StatePublished - 2012

Fingerprint

Dive into the research topics of 'State estimation based on projection observers applied to sequential treatment based on ozonation and aerobic biodegradation: Application for phenolic wastewaters'. Together they form a unique fingerprint.

Cite this