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.