FIELD: automatic optimization of multi-parameter controlled members possessing a single-extreme quality function based on some optimality criterion. SUBSTANCE: the method is realized as follows. In a space of optimized parameters a step is made from the original state in a random direction in accordance with the normal distribution law. If the value of the quality function in the new state exceeds or equals the value of the quality function in the original state (i.e. the random chosen sample turned out to be an unsuccessful one), the system returns to the original state, after which a random step counted off from the old one is formed again. Adaptation of distribution of random steps consists in variation of their mathematical expectation and mean square deviation on the basis of the sign of increment of the quality function. EFFECT: enhanced speed of response of self-adaptation. 1 dwg, 1 tbl
