Parameter identification and state estimation of a microalgae dynamical model in sulphur deprived conditions: Global sensitivity analysis, optimization criterion, extended Kalman filter

Daboussy, Moemen; Titica, Mariana; Boillereaux, Lionel

doi:10.1002/cjce.22007

Cited by 4 publications

(1 citation statement)

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“…An extended Kalman filter estimates the biomass concentration and the extracellular and intracellular sulfur concentration in a closed C. reinhardtii cultivation producing hydrogen [86]. A Droop model with the internal sulfur quota is used as a basis, describing the microalga growth under light attenuation and sulfur-deprived conditions.…”

Section: Kalman Filtersmentioning

confidence: 99%

On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

et al. 2022

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Microalgae are promising sources of fuels and other chemicals. To operate microalgal cultivations efficiently, process control based on monitoring of process variables is needed. On-line sensing has important advantages over off-line and other analytical and sensing methods in minimizing the measurement delay. Consequently, on-line, in-situ sensors are preferred. In this respect, optical sensors occupy a central position since they are versatile and readily implemented in an on-line format. In biotechnological processes, measurements are performed in three phases (gaseous, liquid and solid (biomass)), and monitored process variables can be classified as physical, chemical and biological. On-line sensing technologies that rely on standard industrial sensors employed in chemical processes are already well-established for monitoring the physical and chemical environment of an algal cultivation. In contrast, on-line sensors for the process variables of the biological phase, whether biomass, intracellular or extracellular products, or the physiological state of living cells, are at an earlier developmental stage and are the focus of this review. On-line monitoring of biological process variables is much more difficult and sometimes impossible and must rely on indirect measurement and extensive data processing. In contrast to other recent reviews, this review concentrates on current methods and technologies for monitoring of biological parameters in microalgal cultivations that are suitable for the on-line and in-situ implementation. These parameters include cell concentration, chlorophyll content, irradiance, and lipid and pigment concentration and are measured using NMR, IR spectrophotometry, dielectric scattering, and multispectral methods. An important part of the review is the computer-aided monitoring of microalgal cultivations in the form of software sensors, the use of multi-parameter measurements in mathematical process models, fuzzy logic and artificial neural networks. In the future, software sensors will play an increasing role in the real-time estimation of biological variables because of their flexibility and extendibility.

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Section: Kalman Filtersmentioning

confidence: 99%

On-Line Monitoring of Biological Parameters in Microalgal Bioprocesses Using Optical Methods

et al. 2022

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Software sensors in the monitoring of microalgae cultivations

Porras Reyes,

Havlik,

Beutel

2024

Rev Environ Sci Biotechnol

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Microalgae are well-known photosynthetic microorganisms used as cell factories for the production of relevant biotechnological compounds. Despite the outstanding characteristics attributed to microalgae, their industrial-scale production still struggles with scale-up problems and economic feasibility. One important bottleneck is the lack of suitable online sensors for the reliable monitoring of biological parameters, mostly concentrations of intracellular components, in microalgae bioprocesses. Software sensors provide an approach to improving the monitoring of those process parameters that are difficult to quantify directly and are therefore only indirectly accessible. Their use aims to improve the productivity of microalgal bioprocesses through better monitoring, control and automation, according to the current demands of Industry 4.0. In this review, a description of the microalgae components of interest as candidates for monitoring in a cultivation, an overview of software sensors, some of the available approaches and tools, and the current state-of-the-art of the design and use of software sensors in microalgae cultivation are presented. The latter is grouped on the basis of measurement methods used as software sensor inputs, employing either optical or non-optical techniques, or a combination of both. Some examples of software sensor design using simulated process data are also given, grouped according to their design, either as model-driven or data-driven estimators.

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