Neural networks control of electrical drives under nonlinear loads and parameter variations

Bu çalışma, bilinmeyen ve doğrusal olmayan yükler, sürtünme ve eylemsizlik katsayılarının değişimleri altında vektör kontrollü elektrik motorlarının hız kontrolünü anlatmaktadır. Kontrol yöntemi, Katmanlı Yapay Sinir Ağlarının (KYSA) gerçek zamanda eğitimine dayanmaktadır. İzleme hatası en düşük değerine indirilinceye kadar ağın eğitimine devam edildikten sonra,. küçük izleme ve sürekli rejim hatalarını önlemek için yapay s>inir ağını destekleyen bir integral kompansatör kullanılmıştır. Sürücü sistemlerinin kontrolünde kullanılan KYSA 'nın eğitim problemleri de tartışılmıştır. Çeşitli doğrusal olmayan yük modelleri altında kontrol yöntemi test edilmiş ve KYSA 'nın genelleme performansını gösteren benzetim sonuçları sunulmuştur.

Parametre değişimleri ve doğrusal olmayan yükler altında elektrik sürücülerinin yapay sinir ağları ile kontrolü

This study describes the speed control of vector controlled electrical motors under unknown nonlinear loads, trictional and inertial variations. The control scheme is based on on-line training of a Multi-layer Neural Networks (MNN). After the training, in which the tracking error is minimized, an integral compensator supporting to the MNN is used for eliminating small tracking and steady state errors. Training problems of the MNN in drive systems are also discussed. The control method is tested under wide varieties of nonlinear load models and the simulation results showing the generalization performance of the MNN are presented.

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