Considering the nonlinearity, uncertainty, and rigid/elastic coupling, a state/parameter joint estimation method is essential for control system design or fault diagnosis of flexible hypersonic vehicles. With the goal of improving state/parameter estimation accuracy, this paper proposes a sensor placement strategy and a moving horizon estimation algorithm with a QR-decomposition-based arrival cost update strategy (MHE-QR). To enhance observability, a novel double sensor placement strategy, in which the sensor positions are obtained via solving a constrained nonlinear optimization problem, is developed. The MHE-QR algorithm transforms the arrival cost update problem into a least square problem and solves it utilizing QR decomposition. With this QR-decomposition-based arrival update strategy, the state/parameter estimation problem is solved as a nonlinear programming problem in the framework of moving horizon estimation. Finally, the performance of sensor placement strategy and MHE-QR is evaluated by Monte Carlo simulations in 10 different scenarios. Simulation results demonstrate that the sensor placement strategy and MHE-QR algorithm can effectively improve the estimation accuracy, convergence speed and computation rate. Additionally, the CPU time of MHE-QR validates its real-time applicability.

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In order to solve the attitude control problem of flexible hypersonic vehicles with consideration of aeroservoelastic effect, uncertainty and external disturbance, a novel moving-horizon-estimator-integrated adaptive hierarchical sliding mode control scheme is presented in this paper. First, the measurement model considering flexibility is established and the influence of aeroservoelastic effect on system stability is analyzed. Then moving horizon estimator is developed to reconstruct full state information from sensor measurements, while sliding mode disturbance observer and gain adaptation law is proposed to enhance the robustness and attenuate the chattering. Via combining moving horizon estimator, sliding mode disturbance observer, gain adaptation law and baseline hierarchical sliding mode controller, the moving-horizon-estimator-integrated adaptive hierarchical sliding mode control scheme that is able to achieve the control objective of both precise attitude control and active flexible vibration suppression is developed. Finally, Lyapunov theory is used to prove the stability of the proposed control scheme, and the numerical simulations are carried out, which further verify the effectiveness of the proposed control scheme against aeroservoelastic effect, uncertainty and external disturbance.

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To solve the problem of space targets' trajectory and attitude data generation in system simulation, the characteristics of various types of ballistic missiles and their midcourse targets are analyzed deeply. The baseline ballistic is divided into four types and design methods are given respectively, based on which multiple independently reentry vehicle (MIRV) ballistic design method is established. This method doesn't need preparations and simplifies the system simulation. In addition, an attitude data generation method according to micro-motion characteristic quantity is proposed in order to simulate midcourse target's micro-motion. This method doesn't require numerical integral and speeds up the computation. Simulation results show that four types of baseline trajectory and MIRV trajectory that can accurately hit the target are generated in ten seconds. In addition, the attitude data can reflect the micro-motion characteristic, and the time for data generation is short. This method can meet the requirements of system simulation.