Nonlinear System Identification Based on Genetic Algorithm and Grey Function
The paper presents a method for the identification of nonlinear system parameters by using an improved Genetic Algorithm and Grey Function. The paper firstly outlines several commonly used nonlinear identification methods such as RLS, RIV and COR and also their drawbacks. Then, a method based on the Genetic Algorithm and Grey Function is proposed and given in detail in the paper. Finally, a simulation experiment to TV set production data of an electronic factory was carried out. The simulations show that the method can gain good results and is also simple and effective.
Genetic Algorithm Nonlinear system Grey function
Zhelong Wang Hong Gu
School of Electronic and Information Engineering Dalian University of Technology Dalian, Liaoning, 116024, P.R.CHINA
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）