基于模糊神经网络的岩盐卤水浓度的控制方法研究

RESEARCH ON CONTROL METHOD OF BITTERN DENSITY BASED ON FUZZY NEURAL NETWORK IN SALT SOLUTION MINING

针对岩盐水溶开采中卤水浓度具有慢时变非线性特征 ,设计出一种基于神经网络结构的定常体积下浓度模糊控制与变体积下流量比例因子调节相结合的控制方案 ,所提出的控制模型和学习算法 ,可实现对系统的自适应调整 ,实验结果证明了该方法的有效性 .

Bittern density control in salt solution mining is a slow time delaying and nonlinear process. This paper presents a control method which combines density fuzzy control under constant volume with the regulation of flow proportion factor under variable volume. The method is based on an artificial neural network, whose control model and learning algorithm are also discussed in the paper.Through simulating it is shown that the method is efficient.