针对近空间可变翼高超声速飞行器的非线性系统控制问题, 考虑可变翼对建模的影响、模型参数不确定性和外界未知干扰对跟踪控制性能的影响, 以及虚拟信号多次“微分膨胀”问题, 提出一种基于Back-Stepping的鲁棒自适应动态面控制策略。首先利用插值拟合得到飞行器巡航段的气动参数, 建立精确的纵向模型, 得到飞行器纵向不确定严格反馈块非线性模型。其次根据飞行器的状态变量特性, 将高度和速度分开控制, 利用反步法依次求取控制信号, 并采用RBF神经网络对未知干扰进行逼近, 在线实时更新参数, 实现鲁棒自适应性能。针对虚拟控制信号求导困难和微分膨胀的问题, 加入动态面控制。通过Lyapunov函数等, 证明该方法可以保证系统的半全局稳定有界, 最后通过仿真表明该控制器具有较强的鲁棒性和良好的跟踪性。

To solve the problems of nonlinear system control of the hypersonic morphing vehicle in consideration of the compound disturbances caused by the morphing vehicle, the influence of model uncertainties and unknown outside disturbances, and the “differential expansion” of virtual signals, a robust adaptive dynamic surface control strategy based on back-stepping is proposed.Firstly, the aerodynamic parameters of the morphing vehicle are obtained by curve-fitted approximation, and an accurate longitudinal model is built for the purpose of control design in the hypersonic flight.Secondly, according to the characteristics of the state variables of the aircraft, the speed and height are controlled separately, and the control signals are obtained by using the back-stepping method.The RBF neural network is used to approximate the unknown disturbances, and the parameters are updated in real time to realize the robust adaptive performance.Dynamic surface control is added to solve the problems of derivation and differential expansion of virtual control signals.Finally, Lyapunov function is used to prove that the method can guarantee the semi-global stability of the system, and the simulation results show that the controller has good tracking performance and high robustness.