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The article reviews the task of developing a fuzzy logic PID-type controller for a non-linear dynamic system. The peculiarity of the structure which consists in simplification of its controller by decomposition is presented. The simplest version uses three fuzzy controllers with one input and one output and separate rule bases. The parameters of fuzzy controllers are optimized using a genetic algorithm. A two-step controller setup scheme for a nonlinear dynamic object is proposed. In the first step, the genetic algorithm is used to set up a linear PID-controller, showing that the resulting coefficients are used at the output of each channel of the fuzzy PID-type controller. In the second step, a genetic algorithm forms a nonlinear transformative function for each channel, implemented on the basis of an artificial neural network. The control algorithm is debugged and checked with the MatLab system. The results show a significant improvement in the transition performance compared to traditional controllers.

  • Internet havola
  • DOI
  • UzSCI tizimida yaratilgan sana 06-08-2020
  • O'qishlar soni 484
  • Nashr sanasi 20-05-2020
  • Asosiy tilIngliz
  • Sahifalar102-108
Ўзбек

Maqolada chiziqli bo‘lmagan dinamik tizimlar uchun PID-turli noqat’iy-mantiqiy rostlagichni ishlab chiqish vazifasi ko‘rib chiqilgan. Rostlagich tuzilishini dekompoziciyalarga ajratish orqali soddalashtirish muhim xususiyatlardan biridir. Eng sodda variantda uchta noqat’iy rostlagich bitta kirish, bitta chiqish va alohida qoida bazalari bilan ishlatiladi. Noqat'iy rostlagichlarning parametrlari genetik algoritm yordamida optimallashtirilgan. Chiziqli bo‘lmagan dinamik obyekt uchun ikki bosqichli rostlagichni sozlash sxemasi taklif etiladi. Birinchi bosqichda chiziqli PID-rostlagichni sozlash uchun genetik algoritm qo‘llaniladi, olingan koeffitsientlar noqat’iy PID-rostlagichning har bir kanalining chiqishida ishlatiladi. Ikkinchi bosqichda, genetik algoritmdan foydalanib sun’iy neyron tarmog‘i asosida amalga oshiriladigan har bir kanal uchun chiziqli bo‘lmagan o‘zgartirish funkciyasi hosil bo‘ladi. Matlab dasturi yordamida boshqarish algoritmi tekshirilgan va sinovdan o‘tkazildi. Olingan natijalar an’anaviy rostlagichlarga qaraganda o‘tish jarayonning xususiyatlari sezilarli yaxshilanishini ko‘rsatadi.

 

Kalit so'z
English

The article reviews the task of developing a fuzzy logic PID-type controller for a non-linear dynamic system. The peculiarity of the structure which consists in simplification of its controller by decomposition is presented. The simplest version uses three fuzzy controllers with one input and one output and separate rule bases. The parameters of fuzzy controllers are optimized using a genetic algorithm. A two-step controller setup scheme for a nonlinear dynamic object is proposed. In the first step, the genetic algorithm is used to set up a linear PID-controller, showing that the resulting coefficients are used at the output of each channel of the fuzzy PID-type controller. In the second step, a genetic algorithm forms a nonlinear transformative function for each channel, implemented on the basis of an artificial neural network. The control algorithm is debugged and checked with the MatLab system. The results show a significant improvement in the transition performance compared to traditional controllers.

Русский

В статье рассматриваются результаты решения задачи разработки нечетко-логического регулятора ПИД-типа для нелинейной динамической системы. Представлена особенность структуры, заключающаяся в упрощении ее регулятора путем декомпозиции. В простейшем варианте используются три нечетких регулятора с одним входом и одним выходом и раздельными базами правил. Параметры нечетких регуляторов оптимизируются с использованием генетического алгоритма. Предложена двухшаговая схема настройки регулятора для нелинейного динамического объекта. На первом шаге генетический алгоритм применяется для настройки линейного ПИД-регулятора. Показано, что полученные коэффициенты используются на выходе каждого канала нечеткого регулятора ПИД-типа. На втором шаге с помощью генетического алгоритма формируется нелинейная преобразующая функция для каждого канала, реализуемая на базе искусственной нейронной сети. Алгоритм управления отлажен и проверен с помощью системы MatLab. Полученные результаты показывают значительное улучшение характеристик переходного процесса по сравнению с традиционными регуляторами.

 

 

Kalit so'z
№ Muallifning F.I.Sh. Lavozimi Tashkilot nomi
1 Siddikov I.X. Professor TDTU
2 Umurzakova D.M. докторант TDTU
№ Havola nomi
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