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:  2026
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(.):  power systems, control, optimization, gramian
:   . , , - , . . (generalized pattern search), (particle swarm), (genetic algorithm) (surrogate optimization). . ~ , . , , . ~ MATLAB.
(.):  This paper studies convergence of a few global numerical optimization methods applied to the previously proposed problem of selective damping regulator synthesis based on observability Gramian spectral decomposition. Damping or stabilizing regulators and control in general are used in many applied domains, such as robot actuator control, construction of earthquake and wind resistant buildings and bridges, designing suspension and vibroisolation in transport vehicles. Synthesizing a stabilizing regulator is also of some fundamental theoretical significance in itself. Detailed descriptions of these algorithms are provided. We consider generalized pattern search, particle swarm, genetic algorithm and surrogate optimization. The regulator synthesized is of immediate interest for large scale systems of medium to high order. Therefore, the speed of convergence is important for choosing the optimization method. This study presents the synthesis problem statement, brief descriptions of studied optimization methods, their efficiency analysis for the chosen synthesis problem, and provides practical recommendations for choosing a method depending on the problem.

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