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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。
Aiming at the characteristics of swept-back, non-linear, fast time-varying, strong coupling and uncertainties of variable structure near space vehicles with large enveloping flight, a fully tuned radial basis function neural network Neural Network, FTRBFNN) and robust backstepping robust adaptive tracking control strategy. This method uses FTRBFNN to approach the compound interference in flight-to-flight switching model online. The backstepping method with dynamic surface is applied to design the feedback controller which is suitable for the smooth transition of wing angle after switching. Through the public Lee function, it is proved that the proposed control method can ensure that the output tracking error of the closed-loop switched system converges to any small bounded set within a finite time. Simulation results show that the flight control system has good control performance.