针对航天器系统质量、质心位置和惯性矩阵的在轨辨识问题提出一种解决方法:将系统所有未知参数以组的形式进行划分,每组未知参数都可以转化为线性表示形式,从而将一个非线性系统的参数辨识问题转化为若干个线性的子参数辨识问题;用递推式最小二乘法对每个子参数辨识问题进行求解,在对某组参数求解时所需的其他未知参数则用其估计值代替.通过该方法可将复杂非线性系统转化为若干线性系统实现系统参数在轨辨识.通过数值仿真对采用推进器激励的航天器的总质量、质心位置和惯性矩阵进行辨识,验证了方法的有效性.%Targeting the on-orbit identification of the system mass, the position of the center of mass and the inertia matrix of a spacecraft, a method was proposed in this paper for identifying the un-known parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of the unknown parameters was segmented into a plurality of groups where each individual group of the unknown parameters could be isolated linearly by manipulation of the said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known per-fectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. The validity of this method was verified by numerical simula-tion in identification of the total mass, the position of the center of mass and inertia matrix for a spacecraft with thruster actuation.
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