A study of interceptor attitude control based on adaptive wavelet neural networks

Da Li; Qing-chao Wang

doi:10.1117/12.664520

2 May 2006 A study of interceptor attitude control based on adaptive wavelet neural networks

Da Li, Qing-chao Wang

Proceedings Volume 6042, ICMIT 2005: Control Systems and Robotics; 604208 (2006) https://doi.org/10.1117/12.664520
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China

Abstract

This paper engages to study the 3-DOF attitude control problem of the kinetic interceptor. When the kinetic interceptor enters into terminal guidance it has to maneuver with large angles. The characteristic of interceptor attitude system is nonlinearity, strong-coupling and MIMO. A kind of inverse control approach based on adaptive wavelet neural networks was proposed in this paper. Instead of using one complex neural network as the controller, the nonlinear dynamics of the interceptor can be approximated by three independent subsystems applying exact feedback-linearization firstly, and then controllers for each subsystem are designed using adaptive wavelet neural networks respectively. This method avoids computing a large amount of the weights and bias in one massive neural network and the control parameters can be adaptive changed online. Simulation results betray that the proposed controller performs remarkably well.

Citation Download Citation

Da Li and Qing-chao Wang "A study of interceptor attitude control based on adaptive wavelet neural networks", Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 604208 (2 May 2006); https://doi.org/10.1117/12.664520

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