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研究了系统参数辨识的一种间接方法,该方法将要估计的系统模型转换为一种容易估值的高阶系统模型,然后再将高阶模型降阶得到所要的模型参数。证明了该方法与预报误差法具有相同的渐近和统计性能。仿真结果表明该方法比预报误差法具有更高的计算效率。
An indirect method of system parameter identification is studied. The method converts the system model to be estimated into a high-order system model that is easy to estimate, and then reduces the high-order model to the desired model parameter. It is proved that this method has the same asymptotic and statistical properties of the prediction error method. Simulation results show that this method has higher computational efficiency than the forecast error method.