基于反馈线性化的动能拦截器姿态控制研究

动能拦截器进入末制导阶段时经常需要进行大角度姿态机动,这时拦截器姿态控制系统具有非线性、强耦合、多输入多数出(MIMO)的特点。现针对动能拦截器模型的非线性和不确定性,提出PID神经网络自适应逆控制方法对拦截器飞行姿态进行控制。首先基于精确反馈线性化方法将系统解耦成三个独立的子系统,然后应用基于PID神经网络的自适应逆控制方法分别设计每个子系统的姿态控制器。该方法将PID神经网络控制与自适应逆控制相结合,对于拦截器姿态控制系统中的建模误差以及外部干扰具有较强的适应能力。仿真结果证明了该方法的有效性。

A Study of Kinetic Interceptor Attitude Control System Based on Feedback Linearization

When the kinetic interceptor enters into terminal guidance it has to maneuver with large angles. In this time the characteristic of interceptor attitude system is nonlinearity, strong-coupling and MIMO. A kind of adaptive inverse control approach using PID neural networks for the interceptor attitude uncertain system was proposed in this paper. Based on the exact feedback linearization technique, the system was firstly decoupled into three independent SISO subsystems, and then controllers for each subsystem were designed. The proposed adaptive inverse controllers integrated with PID neural networks make the system robust to the system unknown disturbance. Simulation results show the good performance and effectiveness of the proposed method.