In this study, a low-cost RGB sensor is developed to measure online the microalgae concentration within a photo-bioreactor. Two commercially available devices, i.e., a spectrophotometer for offline measurements and an immersed probe for online measurements, are used for calibration and comparison purposes. Furthermore, the potential of such a sensor for estimating other variables is illustrated with the design of an extended Luenberger observer.
Mathematical modeling and the development of predictive dynamic models are of paramount importance for the optimization, state estimation, and control of bioprocesses. This study is dedicated to the identification of a simple model of microalgae growth under substrate limitation, i.e., Droop model, and describes the design and instrumentation of a lab-scale flat-plate photobioreactor, the associated on-line and off-line instrumentation, the collection of experimental data, and the parameter identification procedure. In particular, a dedicated methodology for parameter identification is discussed, including the determination of an initial parameter set using an analytical procedure, the selection of a cost function, the evaluation of confidence intervals as well as direct and cross-validation tests.
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