基于正交分解的递推子空间闭环辨识方法

为实现闭环系统在线辨识，提出递推正交分解闭环子空间辨识方法(RORT)。首先，根据闭环系统状态空间模型和数据间投影关系，构建确定-随机模型，并利用GIVENS变换实现投影向量的递推QR分解；然后，引入带遗忘因子的辨识算法，构建广义能观测矩阵的递推更新形式，以减少子空间辨识算法中QR分解和SVD分解的计算量；最后，针对某型号陀螺仪闭环系统进行实验。实验结果表明， RORT法的辨识拟合度高于91%，能够对陀螺仪闭环系统模型参数进行在线监测。

Recursive closed-loop subspace identification based on orthogonal decomposition

A closed-loop recursive subspace identification algorithm is proposed to identify the closed-loop systems online by using orthogonal decomposition method. Firstly, the deterministic-stochastic model is built according to the projection relationship among the input, output and exogenous signals, and the recursive QR decomposition is achieved through GIVENS reduction. Then the recursive subspace identification with forgetting factor is used to estimate the extended observability matrix and reduce the computation of QR and SVD decomposition. Finally, the identification experiments are conducted on a gyro closed-loop system. The experiment results show that the identification fitting degree is more than 91% and this algorithm can be used to identify the gyro system model parameters.