Modelling of the automatic stabilization system of the aircraft course by a fuzzy logic method / T. E. Mamonova, V. I. Syryamkin, T. Vasilyeva
Уровень набора: (RuTPU)RU\TPU\network\2008, IOP Conference Series: Materials Science and EngineeringЯзык: английский.Страна: .Серия: Numerical Simulation of Applied ProblemsРезюме или реферат: The problem of the present paper concerns the development of a fuzzy model of the system of an aircraft course stabilization. In this work modelling of the aircraft course stabilization system with the application of fuzzy logic is specified. Thus the authors have used the data taken for an ordinary passenger plane. As a result of the study the stabilization system models were realised in the environment of Matlab package Simulink on the basis of the PID-regulator and fuzzy logic. The authors of the paper have shown that the use of the method of artificial intelligence allows reducing the time of regulation to 1, which is 50 times faster than the time when standard receptions of the management theory are used. This fact demonstrates a positive influence of the use of fuzzy regulation..Примечания о наличии в документе библиографии/указателя: [References: 11 tit.].Тематика: электронный ресурс | труды учёных ТПУ | моделирование | автоматические системы | летательные аппараты | метод нечеткой логики | ПИД-регуляторы | искусственный интеллект | нечеткое регулирование Ресурсы он-лайн:Щелкните здесь для доступа в онлайн | Щелкните здесь для доступа в онлайнTitle screen
[References: 11 tit.]
The problem of the present paper concerns the development of a fuzzy model of the system of an aircraft course stabilization. In this work modelling of the aircraft course stabilization system with the application of fuzzy logic is specified. Thus the authors have used the data taken for an ordinary passenger plane. As a result of the study the stabilization system models were realised in the environment of Matlab package Simulink on the basis of the PID-regulator and fuzzy logic. The authors of the paper have shown that the use of the method of artificial intelligence allows reducing the time of regulation to 1, which is 50 times faster than the time when standard receptions of the management theory are used. This fact demonstrates a positive influence of the use of fuzzy regulation.
Для данного заглавия нет комментариев.