基于拟人智能控制的BTT导弹姿态控制

Attitude Control for Bank-to-turn Missiles Based on Human-imitating Intelligent Control

基于拟人智能控制思想提出一种针对BTT导弹姿态控制的非线性控制律的设计方法。首先利用广义归约的方法将复杂的BTT导弹姿态控制问题分解成若干个可直接解决的本原问题,然后依据各本原问题的主次关系以及耦合关系通过分析导弹的飞行动力学模型设计出非线性控制律结构,最后利用遗传算法将控制律中的各权值优化定量得到定量控制律。该方法适合于对大机动、非线性、强耦合的BTT导弹的姿态控制。仿真结果证明设计的飞行控制律能够在导弹转弯的过程中迅速实现姿态指令的跟踪,并有效的抑制侧滑角的产生。

Based on the human-imitating control, a nonlinear attitude control law for bank-to-turn （BTF） missiles was proposed. The problem of BTT missiles attitude control can be decomposed into several primitive problems by generalized reduction, which can be easily resolved. Then, according to the importance of the primitive problems and the coupling relationship among them, the structure of a nonlinear control law can be given by analyzing the flight dynamic model of the missiles. Finally, the quantitive control law is optimized using the genetic algorithm. The present control is suitable for the attitude control for BTT missiles which are characteristic of high-maneuvering, system nonlinearities and strong coupling. The control law can guarantee the accurate tracking performance of the system while the missile is turning, and besides it can restrain the sideslip efficiently. The simulation results show that the present control law is effective.