Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China.
Sensors (Basel). 2018 Sep 3;18(9):2927. doi: 10.3390/s18092927.
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.
本文研究了与制导控制系统相结合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头伺服系统、导弹制导系统和导弹控制系统（SGCS）的完整模型。其次，设计了一种高阶跟踪微分器（HTD）来实时估计系统状态，保证了所设计算法的可行性。为了保证跟踪精度和鲁棒性，采用了反推滑模控制。针对弹丸运动干扰的主要问题，提出了一种自适应径向基函数神经网络（RBFNN）来补偿干扰。自适应 RBFNN 特别实现了残差的在线调整，提高了估计精度并消除了“抖振现象”。通过李雅普诺夫稳定性理论，特别证明了包括高阶跟踪微分器估计误差在内的所有信号的有界性，更加严格。最后，在所考虑的场景中，进行了视线角（LOSA）跟踪仿真，以验证跟踪性能，并提出了蒙特卡罗脱靶距离仿真，以验证所提出方法的有效性。
