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Control with a model predictive control (MPC) and modelling with artificial neural networks (ANN) of the wire coating process

2010
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Advisor: Prof. Dr. Recep Kozan

Abstract (EN)

This paper presents a new method of modeling the nonlinear parameters of a coating systems base on neural Networks with artificial neural network neurons. Artificial neural networks (ANNs) are a new type of information processing system based on modeling the neural system of human brain. The neural network model shows how the significant parameters influencing thickness can be found. Inthis studies, a back propagation neural network model is developed to map the complex non-linear wire coating thickness between process conditions .Simulations of MPC Control algorithms for coating process have been made and the results of these simulations have been observed. There is a comparison of PID Controller and Generalized Predictive Controller results and there are comments about this comparison in this study. The simulations and calculations of the algorithms have been done in MATLAB environment.

Author

Dr. Bekir Çırak

How to Cite

Bekir Çırak (Doctorate thesis). Control with a model predictive control (MPC) and modelling with artificial neural networks (ANN) of the wire coating process, 2010, Sakarya University.

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