A Fuzzy Neural Network System Modeling Method Based on Data-driven

摘要：

The algorithm utilized only input-output data from the system to determine the proper control model, and not require a mathematical or identified description of the system dynamics. A fusion algorithm that based on subtraction clustering and fuzzy C-means algorithm(FCM) was proposed to identify the former network, automatically obtained precise cluster number and membership parameters, used the steepest descent method to train the weights of the after network, thereby set up a T-S fuzzy neural networks system model, a nonlinear system was used to illustrate this method. Simulation results demonstrate the effectiveness of the proposed identification methods.

关键词： T-S model FCM Fuzzy Neural Network

作者: Keyong Shao Xin Fan Shengmei Han Shaofeng Li

作者单位: College of Electrical and Information Engineering,Daqing Petroleum Institute,Daqing 163318 Qinghai Oil and Gas Development Company,Golmud 816000 PetroChina Co., Ltd. Beijing natural gas pipeline,Yulin 719000

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 624-627

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）