Control system synthesis based on multicriteria optimization using genetic algorithm

The approaches for the parametric synthesis of the automatic control system (ACS) using the genetic algorithm that performs an approximation of Pareto-optimal solutions set are suggested. As a result, two approaches to multi-criteria optimization of ACS were considered: (1) the optimization problem was considered to be three-criteria for equally important criteria, (2) the optimization problem was considered to be two-criteria and a set of Pareto-optimal solutions was obtained for the main criteria. Then, for the final selection, a third criterion was additionally involved, the minimum value of which was sought within the Pareto-optimal set obtained by the main criteria. It is shown that the second approach is preferable to the first one, since it allows obtaining a reasonable solution in a shorter time and with less computational costs. This paper presents the results of multicriteria optimization of the system parameters obtained by MATLAB/Simulink and Global Optimization Toolbox.