Design of BP Neural Network Controller for Infrared Seeker Servo System Based on Stribeck Friction Model

Xin Ying Yan; Bo Mo; Ying He

doi:10.4028/www.scientific.net/AMM.615.409

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 615Design of BP Neural Network Controller for...

Design of BP Neural Network Controller for Infrared Seeker Servo System Based on Stribeck Friction Model

Abstract:

The high precision of the seeker is the key to reduce the Miss-Distance and improve precision in the guidance system of missile, and the seeker stabilized platform servo system is safeguard of the overall performance of seeker. So based on the Stribeck friction model, this paper studies and compares the precision of position and velocity that controlled by PID control and BP neural network when the seeker platform working at low speed. Finally, according to the MATLAB simulation results, applying modern control theory as controller based on Stribeck friction model can improve precision and the problem of flat and dead zone at low speed.

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Periodical:

Applied Mechanics and Materials (Volume 615)

Pages:

409-414

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.615.409

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Online since:

August 2014

Authors:

Xin Ying Yan*, Bo Mo, Ying He

Keywords:

BP Neural Network (BPNN), PID Controller, Seeker, Servo System, Stribeck Friction Model

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* - Corresponding Author

References

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