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A Hierarchical Observer for a Non–Linear Uncertain CSTR Model of Biochemical Processes

Open Access
|Mar 2024

Abstract

The problem of estimation of unmeasured state variables and unknown reaction kinetic functions for selected biochemical processes modelled as a continuous stirred tank reactor is addressed in this paper. In particular, a new hierarchical (sequential) state observer is derived to generate stable and robust estimates of the state variables and kinetic functions. The developed hierarchical observer uses an adjusted asymptotic observer and an adopted super-twisting sliding mode observer. The stability of the proposed hierarchical observer is investigated under uncertainty in the system dynamics. The stability analysis of the estimation error dynamics is carried out based on the methodology associated with linear parameter-varying systems and sliding mode regimes. The developed hierarchical observer is implemented in the Matlab/Simulink environment and its performance is validated via simulation. The obtained satisfactory estimation results demonstrate high effectiveness of the devised hierarchical observer.

DOI: https://doi.org/10.61822/amcs-2024-0004 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 45 - 64
Submitted on: Aug 22, 2023
Accepted on: Dec 8, 2023
Published on: Mar 26, 2024
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2024 Mateusz Czyżniewski, Rafał Łangowski, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.