Interval Self-Organizing Map for Nonlinear System Identification and Control

Authors:
Luzhou Liu;Jian Xiao;Long Yu
Affiliations:
School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China 610031;School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China 610031;School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China 610031
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Year:
2008

Citing 3
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Abstract

The self-organizing map (SOM) is an unsupervised neural network which projects high-dimensional data onto a low-dimensional. A novel model based on interval self-organizing map(ISOM) whose weights are interval numbers presented in this paper differ from conventional SOM approach. Correspondingly, a new competition algorithm based on gradient descent algorithm is proposed according to a different criterion function defined in this paper, and the convergence of the new algorithm is proved. To improve the robustness of inverse control system, the inverse controller is approximated by ISOM which is cascaded with the original to capture composite pseudo-linear system. Simulation results show that the inverse system has superior performance of tracking precision and robustness.