DocumentCode
2972657
Title
Research on Control Method of Complex Object Based on Human Behavior Data
Author
Zhong Bing-xiang ; Li Tai-fu ; Wang De-biao ; Su Ying-ying
Author_Institution
Coll. of Electron. Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China
fYear
2010
fDate
25-27 June 2010
Firstpage
5486
Lastpage
5489
Abstract
In order to simulate human behavior to achieve intelligent control, in this paper a mathematical modeling method is presented based on Kernel Principal Component Analysis (KPCA) and Support Sector Machine. Sample data from the input space are mapped to high-dimensional feature space by non-linear transformation, then their features are extracted by PCA to decrease dimension of input vector and then the modeling based on support vector regression(SVR) are completed. Through the simulation of skilled people to drive a bike, mathematical model of complex system has reconstructed and intelligent control of complex objects is realized. By simulation and testing on experimental systems, the results are proved that the system model has high precision and good control effect.
Keywords
control system analysis; intelligent control; large-scale systems; principal component analysis; regression analysis; support vector machines; bike; complex object; complex system; control method; high-dimensional feature space; human behavior data; intelligent control; kernel principal component analysis; mathematical modeling; nonlinear transformation; support sector machine; support vector regression; Artificial neural networks; Feature extraction; Fuzzy systems; Kernel; Mathematical model; Principal component analysis; Support vector machines; KPCA; SVR; behavior simulation; complex object; feature extraction;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6880-5
Type
conf
DOI
10.1109/iCECE.2010.1333
Filename
5629507
Link To Document