期刊
CONTROL ENGINEERING PRACTICE
卷 85, 期 -, 页码 280-289出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.conengprac.2019.02.003
关键词
Kalman filter; Robust estimation; Sensitivity analysis; Software sensors; Bioprocesses
资金
- FNRS, Belgium
- CONACYT, Mexico
This paper investigates state and unknown input estimations in an Anaerobic Digestion Reactor (ADR) considering a simple two-stage reaction model describing acidogenesis and methanogenesis. From the sole methane outlet flow, this model allows to predict the inlet and outlet biodegradable suspended solid and volatile fatty acid concentrations, which are critical for process stability, as well as acidogenic and methanogenic biomasses. Continuous discrete exogenous and unknown input formulations of the Extended Kalman Filter (EKF) are applied in this context and a numerical robustness analysis is achieved to characterize sensitivities to measurement noise and model uncertainties. The resulting observers are then validated experimentally with data from a lab-scale plant.
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