Proportional integral tuning rules for adaptive neural networks

Steven C. Rogers

doi:10.1117/12.485783

4 August 2003 Proportional integral tuning rules for adaptive neural networks

Steven C. Rogers

Proceedings Volume 5103, Intelligent Computing: Theory and Applications; (2003) https://doi.org/10.1117/12.485783
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Tuning rules for adaptive neural networks have featured Lyapunov-based approaches in recent years. Although these have some desirable qualities they have led to complex tuning procedures. In order to take more advantage of the power of adaptive neural networks less complex and computationally expensive tuning rules are desirable. In addition, tuning rules should be simple and provide for rapid, reliable convergence. In this paper a proportional-integral approach to adaptive neural network tuning rules is studied. Simulation on a nonlinear system is used for a demonstration.

Citation Download Citation

Steven C. Rogers "Proportional integral tuning rules for adaptive neural networks", Proc. SPIE 5103, Intelligent Computing: Theory and Applications, (4 August 2003); https://doi.org/10.1117/12.485783

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