MIMO非线性系统状态估计的递推Monte-Carlo方法研究

Research on Recursive Monte-Carlo Method for MIMO Nonlinear System State Estimation

递推蒙特·卡洛 (Monte-Carlo,MC)方法是基于系统状态和观测值概率分布的估计方法。本文首先讨论了SISO非线性系统状态估计中递推 MC方法的应用 ,在此基础上将上述状态估计方法推广到 MIMO非线性系统 ,并提出了两种不同的估计方案。仿真研究表明 ,这两种方案都可以得到较好的状态估计结果。不过 ,随机抽样数目对递推 MC估计方法的状态估计精度会产生较大影响 ,限制了该方法的进一步应用 ;本文对随机抽样数目对状态估计结果的影响进行了讨论。

Recursive Monte-Carlo (MC) state estimation method based on the statistical probability of state value and observed value is presented for SISO nonlinear system and the method for MIMO nonlinear system state estimation is subsequently proposed with two schemes. Simulation shows that the two schemes estimate the system states quite well. Effect of random sampling number on state estimation is discussed.