GIBRID PID–FUZZY–NEURAL NETWORK ASOSIDA SINXRON MASHINALARNING QO‘ZG‘ATISH TIZIMINI ADAPTIV BOSHQARISH
DOI:
https://doi.org/10.5281/zenodo.23136855Abstract
Sinxron mashinalarning avtomatik qo‘zg‘atish tizimlarini takomillashtirish maqsadida gibrid PID–Fuzzy– Neural Network asosidagi adaptiv boshqaruv usuli taklif etilgan. An’anaviy PID-regulyatorlarning o‘zgaruvchan ish rejimlaridagi samaradorligi hamda elektr energetika tizimlarida yuzaga keladigan tashqi ta’sirlarga sezgirligi tahlil qilingan. Mavjud cheklovlarni bartaraf etish uchun noaniq mantiq (Fuzzy Logic) va sun’iy neyron tarmoqlar (Neural Networks) elementlarini o‘z ichiga olgan intellektual boshqaruv strukturasi ishlab chiqilgan. Mazkur struktura noaniq mantiq algoritmlari yordamida regulyator parametrlarini real vaqt rejimida moslashtirish hamda neyron tarmoq asosida tizim parametrlarining o‘zgarishini prognozlash imkonini beradi. Taklif etilgan boshqaruv usuli generator kuchlanishining o‘tish jarayonlarini yaxshilash, ortiqcha rostlanishni kamaytirish, reaktiv quvvatni samarali boshqarish va energetika tizimining dinamik barqarorligini oshirishga xizmat qiladi.Keywords
sinxron mashina, qo‘zg‘atish tizimi, avtomatik qo‘zg‘atish regulyatori, AVR, PID-regulyator, noaniq mantiq, sun’iy neyron tarmoq, intellektual boshqaruv, adaptiv regulyator, energetika tizimining barqarorligiReferences
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