The Intelligent Control System of Flocculation Process Based on Genetic Wavelet Neural Networks for Sewage Treatment

摘要

Considering the issues that the flocculation process of sewage treatment is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The wavelet neural network has the advantages of both wavelet analysis and neural network, therefore it has the ability of strong nonlinear function approach and the ability of strong adaptive learning and it also has the feature of fast convergence and global optimization. Meanwhile the genetic algorithm has the global search ability. In this paper, an intelligent optimized control system based on genetic wavelet neural network is presented, the parameters of flocculation process are measured using multi sensors, then the control system can control the flocculation process real-time. The system is used in the sewage treatment plant. The experimental results prove that this system is feasible.