SOMA in Real-World Applications

SOMA was used and compared with simulated annealing (SA) and differential evolution (DE) for an engineering application. This application is the automated deduction of fourteen Fourier terms in a radio-frequency (RF) waveform to tune a Langmuir probe. Langmuir probes are diagnostic tools used to determine the ion density and the electron energy distribution in plasma processes. RF plasmas are inherently nonlinear, and many harmonics of the driving fundamental can be generated in the plasma. RF components across the ion sheath formed around the probe distort the measurements made. To improve the quality of the measurements, these RF components can be removed by an active-compensation method. In this research, this was achieved by applying an RF signal to the probe tip that matches both the phase and amplitude of the RF signal generated from the plasma. Here, seven harmonics are used to generate the waveform applied to the probe tip. Therefore, fourteen mutually interacting parameters (seven phases and seven amplitudes) had to be tuned online. In previous work, SA and DE were applied successfully to this problem and hence were chosen to be compared with the performance of SOMA. In this application domain, SOMA was found to outperform SA and DE.
 

Published in:
Nolle, Lars, Ivan Zelinka, Adrian A. Hopgood, and Alec Goodyear. "Comparison of a self-organizing migration algorithm with simulated annealing and differential evolution for automated waveform tuning." Advances in Engineering Software 36, no. 10 (2005): 645-653.

 

Another application was in aircraft wing and mechanical part optimization. The paper deals with a promising approach of modelling the real-life systems, characterized by sets of measured/discrete data, by replacing them with analytical functions framework. The article is focused on the neural network approximation of functional expressions. As an analyzed system, a dynamic flight model has been chosen due to the necessity of considering several classes of large sets of aerodynamic lift, drag, speed, force, balance and mass data to get a comparable mock-up response. Handling such type of model is naturally a huge computation time demanding process. Being able to substitute it with analytical functions system presenting a coincident behaviour could dramatically improve computation time at all aspects of utilization (UAV/UAS, autopilot systems, flight simulators, real-time control and stability response determination, etc.).
 

Published in:
Zelinka, Ivan, Zuzana Oplatková, Pavel Ošmera, Miloš Šeda, and František Včelař. Evoluční výpočetní techniky. BEN, 2008.

 

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