Observability and Identifiability Analyses of Process Models for Agricultural Anaerobic Digestion Plants

TL;DR

This paper analyzes the observability and identifiability of simplified anaerobic digestion models using algebraic and geometric methods, providing insights crucial for process monitoring and control in agricultural biogas plants.

Contribution

It compares algebraic and geometric approaches for assessing model observability, demonstrating the effectiveness of the geometric method for larger models.

Findings

Algebraic assessment is effective for small models like ADM1-R4.

Geometric approach enables observability analysis of larger models.

STRIKE_GOLDD toolbox facilitates complex model analysis.

Abstract

Dynamic operation of anaerobic digestion plants requires advanced process monitoring and control. Different simplifications of the Anaerobic Digestion Model No. 1 (ADM1) have been proposed recently, which appear promising for model-based process automation and state estimation. As a fundamental requirement, observability and identifiability of these models are analyzed in this work, which was pursued through algebraic and geometric analysis. Manual algebraic assessment was successfull for small models such as the ADM1-R4 and simplified versions of the ADM1-R3, which were derived in this context. However, for larger model classes the algebraic approach showed to be insufficient. By contrast, the geometric approach, implemented in the STRIKE_GOLDD toolbox, allowed to show observability for more complex models (including ADM1-R4 and ADM1-R3), employing two independent algorithms. The present study lays the groundwork for state observer design, parameter estimation and advanced control resting upon ADM1-based models.