Adaptive inverse control system based on least squares support vector machines

被引:0
|
作者
Liu, XJ [1 ]
Yi, JQ [1 ]
Zhao, DB [1 ]
机构
[1] Chinese Acad Sci, Inst Automat, Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Adaptive inverse control (AIC) uses three adaptive filters: plant model, controller and disturbance canceller. A kind of hybrid AIC system based on Least Squares Support Vector Machines (LS-SVMs) is proposed in this paper. It has a PID controller to compensate the control signal error. A kind of adaptive disturbance canceller based on LS-SVM is also proposed. It can optimally eliminate plant disturbance. Simulation example is presented to demonstrate that the proposed method works very well.
引用
收藏
页码:48 / 53
页数:6
相关论文
共 50 条
  • [31] Chaos control using least-squares support vector machines
    Suykens, J.A.K.
    Vandewalle, J.
    [J]. International Journal of Circuit Theory and Applications, 27 (06): : 605 - 615
  • [32] Generalized predictive control with online least squares support vector machines
    State Key Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China
    不详
    [J]. Zidonghua Xuebao, 2007, 11 (1182-1188):
  • [33] Chaos control using least-squares support vector machines
    Suykens, JAK
    Vandewalle, J
    [J]. INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 1999, 27 (06) : 605 - 615
  • [34] Optimal control by weighted least squares generalized support vector machines
    Sun, ZH
    Sun, YX
    [J]. PROCEEDINGS OF THE 2003 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2003, : 5323 - 5328
  • [35] Self -Adaptive Parameter Optimization Approach for Least Squares Support Vector Machines
    Li Chun-xiang
    Zhang Wei-min
    Zhong Bi-liang
    [J]. CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 3516 - 3519
  • [36] Least Squares Support Vector Machines for Channel Prediction in the MIMO System
    Martyna, Jerzy
    [J]. DEVELOPING CONCEPTS IN APPLIED INTELLIGENCE, 2011, 363 : 39 - 44
  • [37] Least squares wavelet support vector machines for nonlinear system identification
    Yu, ZH
    Cai, YL
    [J]. ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 2, PROCEEDINGS, 2005, 3497 : 436 - 441
  • [38] Nonlinear system identification using least squares support vector machines
    Zhang, MG
    Wang, XG
    Li, WH
    [J]. PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3, 2005, : 414 - 418
  • [39] Chaos control in lorenz systems based on adaptive inverse control of support vector machines
    Liu, Ding
    Liu, Han
    [J]. PROCEEDINGS OF THE 2006 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL, 2006, : 394 - +
  • [40] Adaptive inverse control for a class of chaotic systems based on support vector machines
    School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China
    [J]. Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2007, 24 (05): : 761 - 765