Modelling of the automatic stabilization system of the aircraft course by a fuzzy logic method; IOP Conference Series: Materials Science and Engineering; Vol. 124 : Mechanical Engineering, Automation and Control Systems (MEACS2015)

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Parent link:IOP Conference Series: Materials Science and Engineering
Vol. 124 : Mechanical Engineering, Automation and Control Systems (MEACS2015).— 2016.— [012075, 6 p.]
Автор: Mamonova T. E. Tatiana Egorovna
Співавтор: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра интегрированных компьютерных систем управления (ИКСУ)
Інші автори: Syryamkin V. I. Vladimir Ivanovich, Vasilyeva T. Татьяна Викторовна
Резюме:Title screen
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.
Мова:Англійська
Опубліковано: 2016
Серія:Numerical Simulation of Applied Problems
Предмети:
Онлайн доступ:http://dx.doi.org/10.1088/1757-899X/124/1/012075
http://earchive.tpu.ru/handle/11683/33857
Формат: Електронний ресурс Частина з книги
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=648545

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330 |a 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. 
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