Genetic search as a tool for overcoming linguistic uncertainty

Abstract

Genetic search as a tool for overcoming linguistic uncertainty

Ignatyev V.V.

Incoming article date: 08.10.2025

This article describes a developed method for automatically optimizing the parameters of an intelligent controller based on an adaptive genetic algorithm. The key goal of this development is to improve the mechanism for generating an intelligent controller rule base through multiparameter optimization. The genetic algorithm is used to eliminate linguistic uncertainty in the design of control systems based on intelligent controllers. A unique algorithm is proposed that implements a comprehensive optimization procedure structured in three sequential stages: identifying optimal control system parameters, optimizing the structure of the intelligent controller rule base, simulating the automatic generation process, and then optimizing the intelligent controller parameters. Implementation of this approach optimizes the weights of fuzzy logic rules and the centers of the membership functions of linguistic variables.

Keywords: intelligent controller, optimization, genetic algorithm, uncertainty, term set