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Next Generation Controlled Environment Agriculture Systems – Multitrophic Production Systems powered by Digital Twins and Advanced Control

Authors: Krujatz, Felix; Streif, Stefan;

Next Generation Controlled Environment Agriculture Systems – Multitrophic Production Systems powered by Digital Twins and Advanced Control

Abstract

The ACSD chair at Chemnitz University of Technology (TUC) is involved in several projects focusing on the valorization of biogenic resources in food and non-food products. Besides method-oriented basic research, the professorship is dedicated to applied research in interdisciplinary projects with academia and industrial partners. Among all, a focus of research is the modelling, control and optimization of various (bio)processes as well as entire process chains and, in particular, closed-loop systems. Dynamic models are derived and artificial intelligence (AI) methods are used, enabling the estimation of process states that are difficult to measure. Based on this, advanced control strategies are designed that enable energy and resource-optimized operation. The ACSD chair has a unique competence profile in the field of dynamic process optimization and AI methods in (alternative) controlled environment agriculture (CEA). In the field of agricultural sciences, for example, expertise is successfully contributed to expert- and data-based prediction modelling, feature extraction and the derivation of optimal controls for multitrophic systems. Digital twins play a crucial role in the digitization and optimization of complex systems. A unique experimental infrastructure is currently being developed at the TUC to enable data acquisition for digital twin design and experimental validation of advanced control strategies under multitrophic process conditions. The talk will present how digitalization tools, in particular AI methodologies can be used to improve the value creation of CEA systems in terms of data acquisition, data management, modelling, process optimization and control as well as operator training, in order to develop circular and energy-efficient production systems for bio-based resources for a circular bioeconomy.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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