A Data-driven Multiple-model Modeling Algorithm

摘要：

Based on the input-output data, a multiple-model modeling method is suggested for the complex nonlinear system. Firstly, fuzzy partition is employed to on-line clustering for the input-output data;and then, the least-squares (LS) algorithm is employed to construct the local model for each clustering, and the parameter of each local model is updated by the new data. The proposed algorithm takes advantage of the TSK model, combines the fuzzy partition and multiple-model modeling, and updates on-line the number of the local model and the parameter of each by the input-output data, so as to realize the on-line modeling for the complex nonlinear system. Simulation result shows the effectiveness of the proposed method.

关键词： nonlinear system multiple models on-line modeling clustering fuzzy partition

作者: Jikun Ye Humin Lei Fei Wang Jiong Li Lei Shao

作者单位: Dept.of Control Science and Engineer Missile Inistitude of Air Force Engineer University Sanyuan,Shanxi

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 98-102

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）