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Design of Three-Dimensional Intelligent Guidance Law for Intercepting Highly Maneuvering Target

Rixin Su, Jinqiang Wang, Shifeng Zhang

IEEE Access · 2023

doi:10.1109/access.2023.3241484 (opens in a new tab)

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Abstract

This paper investigates the three-dimensional guidance and control problem of missile intercepting highly maneuvering target, whose acceleration information is difficult to accurately predict. With the three-dimensional guidance model for intercepting single target established by using the principle of zeroing the rate of line-of-sight (LOS), a novel intelligence guidance law has been designed through backstepping sliding mode control method, radial basis function (RBF) neural network and adaptive control technique. Then, a Lyapunov-based stability analysis demonstrates that all the signals are bounded, and the LOS rates ultimately converge to a neighborhood of the origin. Following advantages are highlighted in this paper: (i) the target information is online estimated and compensated by the RBF neural network, which indicates that the proposed guidance law is easily put into practice only relying on the position information of target. (ii) an adaptive gain term is designed in the control system, which greatly reduces the inherent chattering of sliding mode method. At last, simulations are conducted, and results illustrate the effectiveness and superiority of the designed guidance law.

Abstract licence: CC BY-NC-ND

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