【摘要】 分析了升力式再入飞行器的动力学模型,针对现有的再入控制方法的缺陷,提出了利用神经网络自适应逆来设计再入控制系统,使再入飞行器控制系统克服现有的控制方法的缺陷,无需大量的增益调节,自动适应非线性、强耦合的对象特性,适应大范围环境变化,减小对不同飞行条件下气动与结构参数的依赖性,自动补偿不确定因素。最后通过simulink建模对控制系统进行了仿真,验证了此控制系统能很好地跟踪输入,并且能抑制大范围的外部扰动。更多还原

【Abstract】 The dynamic model of lifting re-entry flight is analyzed and a control method using neural network and adaptive inversion,which is able to overcome the disadvantages of existing control methods,is presented.This method adapted well to nonlinear and strong couple of the plant,and was not sensitive to the variety of environment,disturbances and other uncertainty factors.it was simulated in simulink finally,and the result showed that neural networks and adaptive inversion control can track the desired inputs perfectly.更多还原