弹性高超声速滑翔飞行器的状态/参数联合估计

It is essentially to jointly estimate the state and parameter of flexible hypersonic vehicles due to its nonlinearity, uncertainty, and rigid/elastic coupling. To solve these problems, a sensor placement strategy and a Moving Horizon Estimation with arrival cost updated by QR decomposition (MHE-QR) are proposed. First, the influence of sensor placement on observability is analyzed, based on which a performance index is proposed. Using this performance index, the sensor placement problem is transformed into a constrained optimization problem. The sensor placement scheme is obtained by solving this optimization problem. Utilizing the dynamic programming principle, the MHE-QR algorithm transforms the arrival cost update problem into a least square problem that is solved by QR decomposition in the framework of MHE. The Monte Carlo simulation results demonstrate that the sensor placement strategy and the MHE-QR algorithm can effectively improve the estimation accuracy, convergence speed, and computation rate. Additionally, the CPU time validate the real-time applicability of MHE-QR.