Real-time evolutionary optimization of metallurgical processes using ARM microcontroller

Real-time evolutionary optimization of metallurgical processes using ARM microcontroller

Adam Mrozek1, Wacław Kuś2, Łukasz Sztangret1

1AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland.

22Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, Poland.



The real time (RT) computations with the use of microcontrollers have been present in everyday life for years. They are very useful in e.g. online control of processes due to the ability to determine the proper control in case of any environment changes. The algorithms employed in RT computation must be as simple as possible to meet the imposed time limits. On the other hand, the continuous increase in computational power of modern microcontrollers and embedded platforms causes that more complex algorithms can be performed in the real time. However, during implementation of any algorithm the specific structure and requirements of the microcontroller must be taken into consideration. Another way of fulfilling the time limits of the RT computations is application of metamodel instead of model of controlling process. Within this paper the possibility of application of evolutionary algorithm (EA) to solve three chosen optimization problems in real time using microcontroller of ARM architecture was considered. Analyzed optimization problems were as follows aluminum alloy anti-collision side beam hot stamping process, laminar cooling of dual phase (DP) steel sheets and minimization of the potential energy of the atomic clusters. All computations were performed using two different approaches i.e. low-level and object- oriented approach. Obtained results and drawn conclusions are presented.

Cite as:

Mrozek, A., Kuś, W., Sztangret, Ł. (2016). Real-time evolutionary optimization of metallurgical processes using ARM microcontroller. Computer Methods in Materials Science, 16(1), 20 – 26.

Article (PDF):


Real time computation, Microcontroller, Embedded systems, Optimization of metallurgical processes, Evolutionary algorithm, Metamodel


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