Deep learning based system identification of industrial integrated grinding circuits

2020 ◽  
Vol 360 ◽  
pp. 921-936 ◽  
Author(s):  
Srinivas Soumitri Miriyala ◽  
Kishalay Mitra
2020 ◽  
Vol 53 (2) ◽  
pp. 1175-1181
Author(s):  
Lennart Ljung ◽  
Carl Andersson ◽  
Koen Tiels ◽  
Thomas B. Schön

2020 ◽  
Author(s):  
Brilian Putra Amiruddin

Nowadays, deep learning is the most prominent subjectin the machine learning field. With the bloom of researchers in this field, numerous novel algorithms are used to solve everyday life problems. The control systems field is one of the subjects that get many impacts of machine learning emergence. System identification of Unmanned Aerial Vehicles (UAV) is one of the control systems problems that could be solved by using deep learning methods. In this paper, Recurrent Neural Networks (RNNs) are applied toidentify the system of UAV. Three different models of Deep RNNs have been tried, and the results implied that the RNNs-1 was giving more excellent performance both on the testing MSE and RMSE with the values equal to 0.0006 and 0.0242, successively.


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