Robot kolları için doğrusal süzgeç tabanlı çıkış geri beslemeli kontrolör tasarımında uyarlamalı yöntem yaklaşımı

Yıl 2024, Cilt: 30 Sayı: 6, 756 - 762, 29.11.2024

Bayram Melih Yılmaz , Enver Tatlıcıoğlu

Öz

Bu çalışmada modeli belirsizlikler içeren, pozisyon ölçümleri mevcut
olup, hız ölçümleri olmayan robot kolları için takip problemi ele
alınmıştır. Ölçül(e)meyen hız bilgisinin telafi edilebilmesi için pozisyon
bilgisi tabanlı olarak süzgeçleme tekniği yaklaşımdan
yararlanılmaktadır. Model belirsizlikleri için uyarlamalı sinir
ağlarından yararlanılarak kontrolörün hız ölçümlerine olan
bağımlılığını ortadan kaldırmak için doğrusal süzgeç tabanlı bir
kontrolör tasarlanmıştır. Kapalı çevrim sistemin kararlılığı Lyapunov
yöntemiyle garanti edilmiştir. Sunulan kontrolörün performansını
göstermek için iki serbestlik dereceli robot kolu modeli kullanılarak
sayısal benzetim sonuçları uyarlamalı bulanık mantık yöntemi ile
karşılaştırmalı olarak oluşturulmuştur.

Anahtar Kelimeler

Çıkış geri beslemeli kontrol, Süzgeç tabanlı kontrol, Uyarlamalı sinir ağları, Uyarlamalı bulanık mantık, Lyapunov yöntemleri, Robot kollar

An adaptive method approach in designing a linear filter based output feedback controller for robot manipulators

Öz

This study addresses the tracking problem for robot arms with
parametric uncertainties in the model, position measurements
available, and no velocity measurements. A filtering technique based on
position information is used to compensate for the unmeasured velocity
information. A linear filter-based controller is designed to eliminate the
controller's dependence on velocity measurements by utilizing adaptive
neural networks for model uncertainties. The stability of the closed-loop
system is guaranteed by the Lyapunov method. To demonstrate the
performance of the proposed controller, numerical simulation results
are generated using a two-degree-of-freedom robot arm model and
compared comparatively with adaptive fuzzy logic method.

Anahtar Kelimeler

Output feedback control, Filter based control, Adaptive neural networks, Adaptive fuzzy logic, Lyapunov methods, Robot manipulators.

Kaynakça

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