Neuro-fuzzy systems in modeling devices of unmanned vehicles

The article discusses the role and importance of adaptive neuro-fuzzy systems and fuzzy set theory. The method of determining the truth of the rules is considered, the iterative feature of the algorithm under study is emphasized. Currently, expert systems based on fuzzy rules are used in the automotive, aerospace and transport industries, in the field of household appliances, in finance, analysis and management decision-making, and many others. A practical implementation of the calculation of the function of the fuzzification layer and the functional significance of the mathematical apparatus of the network are given. The importance of the used perceptron in the creation of a fuzzy inference apparatus in digital and analog actuators is emphasized. Fuzzy systems, widely used to understand system behavior, are highly interpretable and able to model human knowledge in understandable linguistic terms. A model for the practical use of the algorithm in simulating the operation of a device in an unmanned vehicle is proposed.