Abstract
The second carbonation in the clarifying process of sugar cane juice is a dynamic nonlinear system which has the characteristics of strong non-linearity, multi-constraint, large time-delay, multi-input and other characteristics of complex nonlinear systems. In this paper, BP neural network is applied to the model of the second carbonation clarifying process of sugar cane juice. The generalized predictive control algorithm is employed to the optional control of color value in clarifying process of second carbonation. The result of Matlab simulation shows that generalized predictive control algorithm based on BP neural network implement the optimal control of the second carbonation with strong robustness and high control precision.
Publisher
Trans Tech Publications, Ltd.
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