变体近空间飞行器的鲁棒自适应控制

摘要

针对变结构近空间飞行器在大包络飞行过程中具有切换的后掠翼、非线性、快时变、强耦合和不确定的特性,提出基于全调节径向基神经网络( Fully Tuned Radial Basis Function Neural Network,FTRBFNN)和动态面backstepping的鲁棒自适应跟踪控制策略.该方法利用FTRBFNN在线逼近飞控切换模型中的复合干扰,应用带有动态面的backstepping方法,设计适用于任意切换后掠翼角光滑的反馈控制器.通过公共李氏函数,证明了所提出的控制方法可以保证闭环切换系统的输出跟踪误差在有限时间内收敛到任意小的有界集内.仿真实验结果表明该飞控系统具有良好的控制性能.%A variable structure near space vehicle has switched wings,nonlinearity,time variability,coupling and uncertainty,especially in large flight envelop. So robust adaptive tracking control is presented based on fully tuned radial basis function neural network (FTRBFNN)and backstepping. Firstly, RBFNN are employed to compensate for unknown disturbance in switched nonlinear systems. Next, adaptive backstepping method is then used to design the smooth feedback controller. Using the common Lyapunov function approach , we prove that the tracking error can converge to an arbitrary small neighborhood of the desired trajectory in a finite time. The simulation results are presented to show the effectiveness of the proposed scheme.