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Adaptive tracking control based on online LS-SVM identifier for unknown nonlinear system

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3 Author(s)
Zhenyan Wang ; School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191 ; Zhen Zhang ; Jianqin Mao

The paper proposes a combined control scheme for completely unknown nonlinear system with an adaptive neural network (ANN) inverse controller based on online least squares support vector machines (LS-SVM) identifier. The neural network controller parameters are adjusted by gradient information of online LS-SVM for the unknown nonlinear system. As well as, considering of the parameter regulating process of ANN, a proportional-integral-derivative (PID) controller is combined to improve the control performance in initial stage. The simulation experiments are made to illustrate the efficiency of the proposed method. The results show that the proposed control method is effective and can achieve better control performance for completely unknown nonlinear system.

Published in:

2012 IEEE International Conference on Information Science and Technology

Date of Conference:

23-25 March 2012