弹性高速飞行器的状态/参数滚动时域估计

Considering the nonlinearity, uncertainty and rigid/elastic coupling of elastic hypersonic vehicles, a state/parameter joint estimation method based on QR decomposition and moving horizon estimation is proposed. First, this method transforms the state/parameter estimation problem into an optimization problem with fixed-number variables by introducing moving horizon strategy, and it can deal with the time-varying parameter estimation better than Kalman filter. Second, by utilizing the forward dynamic programming principle, the computation of arrival-cost is converted into a least-square problem that is solved by QR decomposition, and the arrival-cost update algorithm based on QR decomposition is given. In this way, the moving horizon estimation is based on optimization, and the feedback mechanism is introduced to improve the estimation accuracy and speed. The simulation results demonstrate that the accuracy of moving horizon estimation is obviously higher than that of extended Kalman filter, and the arrival-cost update strategy based on QR decomposition is better than the traditional arrival-cost update method based on the estimated error covariance in speed.