含反馈时滞的非线性动力系统参数辨识

以方程残差作为目标函数，运用基因遗传算法同时辨识受控系统的反馈时滞和物理参数。由于遗传算法具备良好的全局特性，且不要求目标函数光滑，该方法既适于线性系统的辨识也适于非线性系统的时滞辨识，方法中引入几种交叉和变异算子同时操作，大大提高了辨识效率和辨识精度，当需辨识参数过多时，可先用开环实验辨识部分系统参数，再用闭环实验辨识时滞和剩余的系统参数。

Parametric Estimation of Nonlinear Dynamic Systems with Time Delayed Feedback

The experimental modeling of delayed dynamic systems is an open problem.This paper presents an approach based on the genetic algorithms to estimate the system parameters and time delays in the feedback simultaneously through the minimization of residual error of system equation.Several operations such as crossover and mutation are combined so as to improve the convergence rate in the process of parametric estimation.The approach is illustrated by two examples of numerical simulation.Due to the global optimum in a parallel,random and blind way,the approach works for both linear and nonlinear systems with delays.In the case of many system parameters to be estimated,it is suggested to estimate a part of system parameters through an open loop experiment and then the time delays and the remaining parameters through a closed loop experiment.