基于遗传算法的一类不确定性扰动下的系统参数估计

对于线性系统，本文针对其系统矩阵A存在一类不确定性扰动的情况，提出了一种基于遗传算法（GA）的新的参数估计方法。同基于线性矩阵不等式（LMI）的参数估计方法相比，这种方法求解速度快，更适合于高维系统参数估计，为改进仪表测量误差对高维系统建模精度带来的影响提供了一条可行的途径。仿真实验表明，本文提出的方法具有高度鲁棒性和很好精度，能有效地消除不确定性扰动对系统精度的影响。

Parameters Estimation Based on Genetic Algorithms for Systems with Uncertain Disturbance

This paper proposed a new method for parameter estimation based on genetic algorithms (GA) for linear systems in the case of its coefficient matrix with uncertain disturbance. Comparing with the method based on linear matrix inequalities (LMI), it is more fit for estimating the parameter of high dimensional systems for its rapidity. It becomes a feasible approach to improve the modeling precision of high dimensional systems when instruments show measuring deviation. Numerical simulations show that the method proposed in this paper has high robustness, good precision and can restrain the uncertain disturbers influence to the system precision.