Embedded Artificial Neural Network on PLCs to Predict Nonlinear System Responses
Makaleler > Tam Makale · 2020
Yazarlar: Okan DUYMAZLAR, Mustafa ENGİN, Dilşad ENGİN, R Stojanovic, L Jozwiak, Milutinovic, B Lutovac, D Jurisic
2020 9TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO), SCI Expanded İndekslerine Giren Dergi, Uluslararası, Wos, 2020, ss 562-565
Özet
In this study, an artificial neural network, which runs on a real-time controller to obtain outputs of nonlinear multivariable system is presented.Within the scope of the study, forward kinematics problems of a 6 DOF articulated manipulator has been used for the case study of a nonlinear system. An artificial neural network has been trained for forward kinematics problem and implemented on a PLC to predict the responses of the nonlinear systems on real-time. Also an HMI was used for the observation of system responses and serve as an input device.As a conclusion, an embedded real-time system that successfully works with trained artificial neural network, has been implemented on a common nonlinear case.