基于神经网络的柠檬酸蒸发过程的优化控制

针对柠檬酸双效蒸发器存在关联耦合严重、环境干扰不确定、非线性、时滞等现象，采用软测量技术建立其完成液浓度的神经元网络模型，在此基础上运用混沌优化法进行了稳态优化控制研究。结果表明，该方法易于程序实现、求解精度高，已取得较好的节能效果，并提出了在线优化控制的建议。

Optimization Control of the Citric Acid Evaporation Process Based on Neural Network

The authors employ soft-measuring technique to build a neural network model for solution dense test to overcome the shortcomings of the citric acid double-efficiency evaporator such as serious relevance, uncertainty to the interference of its surroundings and non-linear and time-delay objects. Besides, we also use chaoticoptimization to study optimal control of stable status based on the previous model. The experimental results show that our approach is apt to implementation by programming, gets solutions of high precision and is good for saving energy. In the last part of our paper, we give some comments on linear optimal control.