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Xiaobin Qian, Helong Shen, Yong Yin and Dongdong Guo
In this paper, we present a novel nonlinear model predictive control (NMPC) algorithm based on the Laguerre function for dynamic positioning ships to solve the problems of input saturation, unknown time-varying disturbances, and heavy computation. The no...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Francisco Alonso, Benjamín Samaniego, Gonzalo Farias and Sebastián Dormido-Canto
This article provides a general overview of the communication protocols used in the IEC61850 standard for the automation of electrical substations. Specifically, it examines the GOOSE and R-GOOSE protocols, which are used for exchanging various types of ...
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Hugo Valayer, Nathalie Bartoli, Mauricio Castaño-Aguirre, Rémi Lafage, Thierry Lefebvre, Andrés F. López-Lopera and Sylvain Mouton
In aerodynamics, characterizing the aerodynamic behavior of aircraft typically requires a large number of observation data points. Real experiments can generate thousands of data points with suitable accuracy, but they are time-consuming and resource-int...
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Yiyuan Xu, Jianhui Zhao, Biao Wan, Jinhua Cai and Jun Wan
Flood forecasting helps anticipate floods and evacuate people, but due to the access of a large number of data acquisition devices, the explosive growth of multidimensional data and the increasingly demanding prediction accuracy, classical parameter mode...
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