基于卡尔曼滤波和随机逼近的模拟器时间延迟补偿方法

针对飞行模拟器的时间延迟补偿问题,采用卡尔曼滤波和随机逼近的方法,提出了自适应遗忘因子卡尔曼补偿法和自适应遗忘因子随机逼近补偿法,这2种方法通过预测偏差动态调节遗忘因子的大小,可以提高预测精度并减小预测偏差;在2种补偿法的收敛矩阵初始值中引入调节参数,避免了初始值发生奇异现象;并且与改进的McFarland补偿方法进行了比较.结果表明,这2种方法的预测偏差分别小于相对应的改进的McFar-land补偿方法的预测偏差,且自适应遗忘因子卡尔曼补偿法是4种方法中最优的补偿方法.

Transport Delay Compensation Algorithm for Simulator Based on Kalman Filter and Stochastic Approximation Algorithm

In order to compensate transport delay of flight simulator,two transport delay adaptive forgetting factor compensation algorithms based on Kalman filter and Stochastic Approximation are presented.To improve prediction of precision and reduce errors,the time varying forgetting factor is regulated by the error,and a regulatory parameter is added in the initial parameter matrix of the two compensation algorithms,the singularity in the initial parameter matrix is avoided.The results imply that the two algorithms are superior to the algorithms of the revised McFarland and the Kalman filter compensation algorithm is the most excellent among the four types of algorithms.