Adaptive neural network nonlinear control for BTT missile based on the differential geometry method

Hao Wu; Yongji Wang; Jiangsheng Xu

doi:10.1117/12.750634

15 November 2007 Adaptive neural network nonlinear control for BTT missile based on the differential geometry method

Hao Wu, Yongji Wang, Jiangsheng Xu

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678822 (2007) https://doi.org/10.1117/12.750634
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

A new nonlinear control strategy incorporated the differential geometry method with adaptive neural networks is presented for the nonlinear coupling system of Bank-to-Turn missile in reentry phase. The basic control law is designed using the differential geometry feedback linearization method, and the online learning neural networks are used to compensate the system errors due to aerodynamic parameter errors and external disturbance in view of the arbitrary nonlinear mapping and rapid online learning ability for multi-layer neural networks. The online weights and thresholds tuning rules are deduced according to the tracking error performance functions by Levenberg-Marquardt algorithm, which will make the learning process faster and more stable. The six degree of freedom simulation results show that the attitude angles can track the desired trajectory precisely. It means that the proposed strategy effectively enhance the stability, the tracking performance and the robustness of the control system.

Citation Download Citation

Hao Wu, Yongji Wang, and Jiangsheng Xu "Adaptive neural network nonlinear control for BTT missile based on the differential geometry method", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678822 (15 November 2007); https://doi.org/10.1117/12.750634

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