Recurrent Neural Networks Biomass Observer for Anaerobic Processes

Diana A. Urrego-Patarroyo, E. Sánchez, S. Carlos-Hernandez, J. Béteau
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引用次数: 4

Abstract

In this paper, a recurrent neural networks observer for anaerobic processes is proposed; the main objective is to estimate biomass, in a completely stirred tank reactor. The neural network is trained with an extended Kalman filter algorithm. The applicability of the proposed observer is verified via simulations.
厌氧过程的循环神经网络生物质观测器
本文提出了厌氧过程的递归神经网络观测器;主要目的是在完全搅拌的槽式反应器中估计生物量。神经网络采用扩展卡尔曼滤波算法进行训练。通过仿真验证了所提观测器的适用性。
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