Multi-sensor Optimal H ∞ Fusion Filters for a Class of Nonlinear Intelligent Systems with Time Delays

Authors:
Meiqin Liu;Meikang Qiu;Senlin Zhang
Affiliations:
College of Electrical Engineering, Zhejiang University, Hangzhou, China 310027 and Department of Electrical Engineering, University of New Orleans, New Orleans, USA LA 70148;Department of Electrical Engineering, University of New Orleans, New Orleans, USA LA 70148;College of Electrical Engineering, Zhejiang University, Hangzhou, China 310027
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

Citing 4
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Multi-sensor optimal H∞ fusion filters for delayed nonlinear intelligent systems based on a unified model

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Abstract

This paper proposes a nonlinear system model, which is composed of a linear time-delay dynamic system and a bounded static nonlinear operator. Base on the H ∞ performance analysis of this nonlinear model, H ∞ fusion filter is designed for this model with multiple sensors to guarantee the asymptotic stability of the fusion error system and reduce the effect of the noise signals on the filtering error to a lowest level. The parameters of the filter are obtained by solving the eigenvalue problem (EVP). Some delayed (or non-delayed) intelligent systems composed of neural networks or Takagi and Sugeno (T-S) fuzzy models can be transformed into this nonlinear model, then the multi-sensor optimal H ∞ fusion filters for them are designed.