【作者】 梁海葵；

【导师】 何小阳；

【作者基本信息】 广西大学 ， 控制理论与控制工程， 2008， 硕士

【摘要】 蒸发工段是制糖工艺的关键步骤。对蒸发工段的有效控制,首先保证了末效出口糖浆浓度的稳定,满足煮糖工段对工艺的要求;同时减少了能量的消耗,具有显著的经济效益。因而研究蒸发工段多效蒸发系统的建模与控制对于具有重要意义。在了解了蒸发工艺流程和多效蒸发原理的基础之上,根据多效蒸发系统强干扰、非线性、多约束等特点,利用BP人工神经网络建立了多效蒸发系统二效压力和末效出口糖浆浓度之间的人工神经网络模型。系统仿真实验显示,建立的模型具有较好的逼近能力,能够较好的反映系统末效出口糖浆浓度的输出特性。论文的另一部分工作是介绍了预测控制算法,对非线性预测控制在多效蒸发系统中的应用进行了深入的研究和探讨,提出了以BP神经网络建立预测模型、遗传算法进行滚动优化的预测控制算法。以所建的神经网络模型作为对象对多效蒸发系统实施非线性预测控制仿真。仿真结果表明,控制效果较好,可以达到控制要求。更多还原

【Abstract】 The evaporator station is a key process step in the cane sugar mill. Its robust control is essential to guarantee the output syrup concentration as close as possible to the desired values to feed to the crystallization process and optimize the energy used. Therefore, modeling and control of the evaporating process is of the highest importance in the sugar industry.On the basis of comprehension of the evaporating process flow and principle of multiple-effect evaporation, according to the following plant features: strong disturbances, great nonlinearity, many constrains and so on, The error BP(BackProragation)neural network is used to establish a model and describe the complex relationship among the juice steam pressure of the second stage and the syrup brix leaving the multiple-effect evaporator. The simulation result proves the validity of the model which has strong ability to describe the multiple-effect evaporation and reveal the performance of the syrup brix leaving the multiple-effect evaporator.The predictive control algorithm is introduced in another part of the dissertation, and analyze application of nonlinear MPC in cane sugar multiple-effect evaporation, then a MPC algorithm which based on BP neural network model and genetic algorithm optimization is discussed. A simulation has been taken to the multiple-effect evaporation by means of nonlinear MPC algorithms. From simulation result, it receives good effect and reaches the requirement of control.更多还原