Mathematic Model and Optimal Control Method Based on Hybrid Intelligent System

摘要：

A mathematic model based on RBF neural network and genetic algorithm for multivariable optimal control with the lowest operational cost by limiting total substrate discharge in activated sludge process are discussed in this paper. It shows that the RBF neural network has preferable convergence for modeling the process. Genetic algorithm is an effective searching method to resolve the optimal problem in this case. Based on satisfying the requirements of precision, binary coding is used to express units, and 20 bits of binary digits express DO, Qw separately. According to the adaptive degree of units, which can be operated genetically through genetic operator, superior units can be saved, inferior ones are eliminated, and a group of new units can be obtained. The optimization strategy made up of RBF neural network and genetic algorithms is adopted. After achieving the discharge standard of biochemical oxygen demand, the control rule for variables to make operation cost be least is found.

关键词： mathematic model RBF neural network genetic algorithm sewage disposal activated sludge process

作者: LIU Zaiwen WANG Xiaoyi HOU Chaozhen CUI Lifeng XUE Hong WU Yelan

作者单位: School of Information Science and Technology Beijing Institute of Technology Beijing,100081,China;Sc School of Information Science and Technology Beijing Institute of Technology Beijing,100081,China School of Information Engineering Beijing Technology and Business University Beijing, 100037, China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 435-440

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）