本文基于正交计算灵敏度的极大似然估计算法研究了弹性飞行器的气动参数辨识问题。
In this paper, the aerodynamic parameter identification of elastic aircraft is studied by the maximum likelihood estimation algorithm using, orthogonal test table for computing sensitivities.
此算法基于极大似然算法将等距线阵均分为三个子孔径，从而简化了估计函数，也使计算量大大减少。
Base on the maximum likelihood algorithm, the algorithm divides an array into three subaperture and predigests the estimate function and reduces the compute quantity.
研究了广义预测控制的模型反馈校正方法，将递推极大似然法和遗忘因子递推最小二乘法结合起来，给出了一种改进的递推极大似然参数估计算法。
Model feedback correction algorithm of GPC has Benn studied. Combining the RML and forgetting factor RLS, an improved RML parameter estimation method has been given.
研究了广义预测控制的模型反馈校正方法，将递推极大似然法和遗忘因子递推最小二乘法结合起来，给出了一种改进的递推极大似然参数估计算法。
Model feedback correction algorithm of GPC has Benn studied. Combining the RML and forgetting factor RLS, an improved RML parameter estimation method has been given.
应用推荐