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针对高超声速飞行器部分状态发生不可测量问题,提出基于观测器的系统控制器设计。将所设计的被观测系统在某平衡点处线性化,用Luenberger观测器理论设计观测器增益,得到渐近收敛于系统真实状态的状态观测值。采用状态观测器与控制器分开设计的方法,应用反演控制技术,引入指令滤波器,使得伪控制量的导数可以轻易获得,简化了设计。针对系统中存在高频未建模动态,采用RBF神经网络对其进行逼近,以增强系统的跟踪性能。利用Lyapunove稳定性理论保证闭环系统有界且跟踪误差收敛于原点附近的小邻域内。通过在六自由度模型上的仿真,表明了所提方法的可行性与有效性。
Aiming at the unmeasurable state of hypersonic vehicle state, the observer-based system controller design is proposed. The designed system is linearized at a certain equilibrium point, and the observer gain is designed by using Luenberger observer theory to get the state observation asymptotically converging to the real state of the system. Using the method of state observer and controller separately design, the inversion control technique is introduced and the command filter is introduced to make the derivatives of pseudo-control quantities easy to obtain and simplify the design. Aiming at the unmodeled high-frequency dynamics in the system, RBF neural network is used to approach it to enhance the tracking performance of the system. The Lyapunove stability theory is used to ensure the closed-loop system is bounded and the tracking error converges to a small neighborhood near the origin. The simulation on six degrees of freedom model shows the feasibility and effectiveness of the proposed method.