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Backstepping Sliding Mode Control for Radar Seeker Servo System Considering Guidance and Control System

机译:考虑制导和控制系统的雷达搜索器伺服系统的后推滑模控制

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摘要

This paper investigates the design of a missile seeker servo system combined with a guidance and control system. Firstly, a complete model containing a missile seeker servo system, missile guidance system, and missile control system (SGCS) was creatively proposed. Secondly, a designed high-order tracking differentiator (HTD) was used to estimate states of systems in real time, which guarantees the feasibility of the designed algorithm. To guarantee tracking precision and robustness, backstepping sliding-mode control was adopted. Aiming at the main problem of projectile motion disturbance, an adaptive radial basis function neural network (RBFNN) was proposed to compensate for disturbance. Adaptive RBFNN especially achieves online adjustment of residual error, which promotes estimation precision and eliminates the “chattering phenomenon”. The boundedness of all signals, including estimation error of high-order tracking differentiator, was especially proved via the Lyapunov stability theory, which is more rigorous. Finally, in considered scenarios, line of sight angle (LOSA)-tracking simulations were carried out to verify the tracking performance, and a Monte Carlo miss-distance simulation is presented to validate the effectiveness of the proposed method.
机译:本文研究了结合制导和控制系统的导弹导引头伺服系统的设计。首先,创造性地提出了一个包含导弹导引系统,导弹制导系统和导弹控制系统(SGCS)的完整模型。其次,采用设计的高阶跟踪微分器(HTD)实时估计系统状态,从而保证了所设计算法的可行性。为了保证跟踪精度和鲁棒性,采用了后推滑模控制。针对弹丸运动扰动的主要问题,提出了一种自适应径向基函数神经网络(RBFNN)来补偿扰动。自适应RBFNN尤其可以实现残差误差的在线调整,从而提高了估计精度并消除了“抖动现象”。特别是通过更严格的Lyapunov稳定性理论证明了所有信号的有界性,包括高阶跟踪微分器的估计误差。最后,在考虑的情况下,进行了视线(LOSA)跟踪仿真以验证跟踪性能,并提出了蒙特卡洛失距仿真以验证该方法的有效性。

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