A cooperative neural network control structure and its application for systems having dead-zone nonlinearities
Yükleniyor...
Tarih
2022-03
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer International Publishing Ag
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
An adaptive control structure utilizing two feed-forward neural networks (NN) is proposed to deal with systems having unknown nonlinearities. One of the networks is trained to mimic the nonlinear system dynamics. Its training will be repeated with periods in order to keep it an updated valid model of the system all the times since the parameters and/or nonlinearities of the system may change during time. The other network, which is the Controller NN, adapts itself continuously by collaborating with the Model NN. The stability-convergence analysis of both networks is performed via Lyapunov method. An example system is chosen to show the applicability of the control algorithm. This example system is created by combining a linear dynamics model with a dead-zone function to represent a nonlinear system to be controlled. It should be noted that the proposed control structure can be used in any nonlinear system without knowing the system dynamics. The only information required by Model NN is the training set consisting input-output data pairs of the system. The Model NN is trained offline with this training set, and afterward the Controller NN adapts its weights online continuously during the control task with the help of Model NN. The performances of PD and PID controllers are also given for comparison purposes.
Açıklama
Anahtar Kelimeler
Actuator, Adaptive control, Dead zone, Discrete-time-systems, Dynamic surface control, Identification, Machine learning, Neural network control, Tracking control
Kaynak
Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
46
Sayı
1
Künye
Dinçmen, E. (2022). A cooperative neural network control structure and its application for systems having dead-zone nonlinearities. Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, 46(1), 187-203. doi:10.1007/s40998-021-00475-0
