离散不确定系统的优化鲁棒滤波方法及在飞行试验中的应用

提出了一种离散系统的优化鲁棒滤波方法。为了得到滤波的逼近计算式，通过优化加权矩阵得到了上界不等式逼近和等效系统矩阵，得到了鲁棒滤波的时间更新算法；通过优化加权矩阵得到了下界不等式逼近和等效观测矩阵，得到了鲁棒滤波的测量更新算珐，并且给出了鲁棒滤波算法收敛的条件。飞行试验数据处理的结果表明，提出的方法是有效的。

Optimized Robust Filter for Uncertain Discrete Time System and Its Application to Flight Test

An optimized robust filtering algorithm for uncertain discrete time systems is presented. To get a series of computational equations, the uncertain part generated by the uncertain systematic matrix in the expression of the error covariance matrix of time update state estimation is optimized and the least upper bound of the uncertain part is given. By means of these results, the equivalent systematic matrix is obtained and a robust time update algorithm is built up. On the other hand, uncertain parts generated by the uncertain observation matrix in the expression of the error covariance matrix of measurement update state estimation are optimized, and the largest lower bound of the uncertain part is given. Thus both the time update and measurement update algorithms are developed.By means of the matrix inversion formula, the expression structures of both time update and measurement update algorithms are all simplified. Moreover, the convergence condition of a robust filter is developed to make the results easy to application. The results of flight data processing show that the method presented in this paper is efficient.