Intelligent Control of Flocculation Process Based on Radial Basis Probabilistic Neural Network for Sewage Treatment

摘要：

　　The flocculating process of sewage treatment is a complicated and nonlinear system,and it is very difficult to found the process model to describe it.The radial basis probabilistic neural network (RBPNN) has the ability of strong function approach and fast convergence.In this paper,an intelligent optimized control system based on radial basis probabilistic neural network is presented.We constructed the structure of radial basis probabilistic neural network that used for controlling the flocculation process,and adopt the K-Nearest Neighbor algorithm and least square method to train the network.We given the architecture of control system and analyzed the working process of system.In this system,the parameters of flocculation process were measured using sensors,and then the control system can control the flocculation process real-time.The system was used in the sewage treatment plant.The experimental results prove that this system is feasible.

关键词： Flocculation process Control Radial basis probabilistic network Sewage treatment

作者: Jingwen Tian Meijuan Gao

作者单位: Beijing Union University, Beijing, 100101, China

会议类型: 国际会议

会议名称: the 2010 International Conference on Frontiers of Manufacturing and Design Science(第一届制造与设计科学国际会议(ICFMD 2010))

会议地点: 重庆

会议语种:英文

页码: 3289-3293

在线出版日期: 2010-12-11（万方平台首次上网日期，不代表论文的发表时间）