随机自治状态空间模型的正交梯度辨识

提出了随机自治系统参数的正交梯度二步递阶优化方法．通过极小化输出预报误差得到了系统参数估计；给出了正交梯度搜索方法用于解决系统参数的非唯一性问题，系统参数的二步递阶优化辨识方法包括两步：首先用给出的自适应L-M算子正交梯度方法确定参数优化方向；其次由一维搜索方法计算最佳步长．蒙特-卡罗数值仿真试验表明本文提出的方法具有收敛速度快、抗噪能力强以及数值稳定性好等优点．

Hierarchical optimization identification of stochstic state-space systems by projected gradient search

A hierarchical optimization method for the identification of stochastic autonomous state-space systems was proposed in terms of projected gradient search. The system parameters were determined by optimizing an output-error cost function. For the consideration of non-uniqueness of the fully parameterized system, a projected gradient search algorithm was presented by restricting the update of the parameters to the tangent space to the manifold of observationally equivalent state-space systems. The proposed hi...