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The component concentrations measurement of sodium aluminate solution are critical to the process of alumina production, they affect the product quality. However, they can not be measured online at present, thus the control and optimal operation is hardly to be achieved. This paper presents an on-line fuzzy modeling method to predict the component concentrations. It includes an on-line clustering...
In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate production plants. Several advance techniques are used, such as PLS (Partial Least Squares), Hammerstein model, recurrent neural networks and least square algorithm. Industrial experiment...
The component concentrations in sodium aluminate solution are very important in the process of alumina production, they represents the product quality. At present they can not be measured online, so the optimal operation is hardly to be achieved. To deal with this problem and based on the character of process industry data, we propose a RKPLS (Robust Kernel Partial Least Squares) soft sensing method...
Process data exhibits both nonlinear and dynamic characteristics. A multivariable nonlinear dynamic modeling method is proposed by combining dynamic partial least squares (DPLS) algorithm and Hammerstein model. This method applies Hammerstein model to the DPLS inner regression. The outer PLS algorithm with ARX inputs is used to model the dynamics of the process, and it is also used to reduce the dimensionality...
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