Autonomous Processes in Particle Technology - Research and Testing of Concepts for Model-based Control of Particulate Processes (SPP 2364)
Termin:
15.12.2021
Fördergeber:
Deutsche Forschungsgemeinschaft (DFG)
In March 2021, the Senate of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) established the Priority Programme "Autonomous Processes in Particle Technology - Research and Testing of Concepts for Model-based Control of Particulate Processes" (SPP 2364). The programme is designed to run for six years. The present call invites proposals for the first three-year funding period.
Due to the distributed properties of particles, their processing often prevents extensive automation and autonomous process control, which stands for an autonomous adjustment of the product properties without external intervention. The goal of the Priority Programme is therefore the research and the testing of methods for an autonomous process control in particle technology. The focus is on the coupling of the material and data streams of the respective unit operations with measurement technology, modelling and control algorithms to form a closed loop for model-based control. After termination of the programme, a new type of "box of scientific tools" (methods, algorithms, models, data structures and information architectures) should be available, which will allow a reliable process control where the tool can also be transferred to new particle processes.
The structure of the Priority Programme is divided into three topics:
o Development of controllable process models (modelling)
The consideration of time dependent property distributions leads to mathematically demanding process models. A direct use in model-based process control is often prevented by a lack of real-time capability. Therefore, the topic of process modelling is focused on the development of dynamic process models, which can be used for process control. Due to the often complex relationships between particle and product properties, the use of data-driven or combined methods (semi-parametric models) seems appropriate, e.g. a simulative approach based on balance equations connected with a machine learning algorithm, which takes specific material properties into account (grey-box modelling).
o Measuring systems for the in-situ acquisition of product properties (measurement technology)
For the successful implementation of process control, information about the process state is necessary. Therefore, the overall objective of this topic is the development of real time capable in-situ measurement techniques for the direct acquisition of distributed product properties. This can be done on the one hand by direct data acquisition, on the other hand by combining the correlation between measured particle properties and the associated product properties in a model-based measurement system (soft sensors). The development of model-based systems for the detection of disturbances in processes is also part of this topic. If necessary, the measuring systems themselves are to be considered as dynamic systems in the process chain. In addition, limits for the uncertainties of the measurement systems could also be part of an investigation.
o Development of concepts for model-based control of particle technology processes (process control)
The goal in this topic is the development and implementation of control concepts for single-stage and, in a further step, multi-stage particle processes (process chain). The main tasks of control are the automatic adjustment of the desired particle and product properties, the compensation of unforeseen disturbances, the acceleration of start-up and shut-down as well as the planning and control of optimal trajectories of batch processes under consideration of uncertainties and process-relevant quality criteria (e.g. energy and raw material efficiency). Methodically, methods of nonlinear, optimisation based and robust control can be applied.
A project focus can be on one of the three topics process model - measurement technology - process control, but should have a visible reference to the autonomous process control of particle processes. In particular, the closed loop, i.e. the interconnection of the three topics, is the basic structural element that must be present in each project and, at an advanced stage, the interconnection to form a process chain. In principle, the projects can be handled by a single applicant from the above mentioned disciplines. It is also desired that a project is carried out in close cooperation between the disciplines with the respective project focus for the description of the processes or the process chain (tandem projects).
Applicants must be registered in elan prior to submitting a proposal to the DFG. If you have not yet registered, please note that you must do so by 1 December 2021 to submit a proposal under this call; registration requests received after this time cannot be considered.
Questions on the DFG proposal process can be directed to:
Dr. Simon Jörres
phone +49 228 885-2971
simon.joerres@dfg.de
Further Information:
https://www.dfg.de/foerderung/info_wissenschaft/ausschreibungen/info_wissenschaft_21_57/index.html
Due to the distributed properties of particles, their processing often prevents extensive automation and autonomous process control, which stands for an autonomous adjustment of the product properties without external intervention. The goal of the Priority Programme is therefore the research and the testing of methods for an autonomous process control in particle technology. The focus is on the coupling of the material and data streams of the respective unit operations with measurement technology, modelling and control algorithms to form a closed loop for model-based control. After termination of the programme, a new type of "box of scientific tools" (methods, algorithms, models, data structures and information architectures) should be available, which will allow a reliable process control where the tool can also be transferred to new particle processes.
The structure of the Priority Programme is divided into three topics:
o Development of controllable process models (modelling)
The consideration of time dependent property distributions leads to mathematically demanding process models. A direct use in model-based process control is often prevented by a lack of real-time capability. Therefore, the topic of process modelling is focused on the development of dynamic process models, which can be used for process control. Due to the often complex relationships between particle and product properties, the use of data-driven or combined methods (semi-parametric models) seems appropriate, e.g. a simulative approach based on balance equations connected with a machine learning algorithm, which takes specific material properties into account (grey-box modelling).
o Measuring systems for the in-situ acquisition of product properties (measurement technology)
For the successful implementation of process control, information about the process state is necessary. Therefore, the overall objective of this topic is the development of real time capable in-situ measurement techniques for the direct acquisition of distributed product properties. This can be done on the one hand by direct data acquisition, on the other hand by combining the correlation between measured particle properties and the associated product properties in a model-based measurement system (soft sensors). The development of model-based systems for the detection of disturbances in processes is also part of this topic. If necessary, the measuring systems themselves are to be considered as dynamic systems in the process chain. In addition, limits for the uncertainties of the measurement systems could also be part of an investigation.
o Development of concepts for model-based control of particle technology processes (process control)
The goal in this topic is the development and implementation of control concepts for single-stage and, in a further step, multi-stage particle processes (process chain). The main tasks of control are the automatic adjustment of the desired particle and product properties, the compensation of unforeseen disturbances, the acceleration of start-up and shut-down as well as the planning and control of optimal trajectories of batch processes under consideration of uncertainties and process-relevant quality criteria (e.g. energy and raw material efficiency). Methodically, methods of nonlinear, optimisation based and robust control can be applied.
A project focus can be on one of the three topics process model - measurement technology - process control, but should have a visible reference to the autonomous process control of particle processes. In particular, the closed loop, i.e. the interconnection of the three topics, is the basic structural element that must be present in each project and, at an advanced stage, the interconnection to form a process chain. In principle, the projects can be handled by a single applicant from the above mentioned disciplines. It is also desired that a project is carried out in close cooperation between the disciplines with the respective project focus for the description of the processes or the process chain (tandem projects).
Applicants must be registered in elan prior to submitting a proposal to the DFG. If you have not yet registered, please note that you must do so by 1 December 2021 to submit a proposal under this call; registration requests received after this time cannot be considered.
Questions on the DFG proposal process can be directed to:
Dr. Simon Jörres
phone +49 228 885-2971
simon.joerres@dfg.de
Further Information:
https://www.dfg.de/foerderung/info_wissenschaft/ausschreibungen/info_wissenschaft_21_57/index.html