区间卡尔曼滤波算法在参数估计中的应用

Application of Interval Kalman Filtering Algorithm to Parameter Estimation

卡尔曼滤波算法除了用于动态系统的状态估计外,还可以用于动态系统参数的在线估计,特别是时变参数的估计。传统卡尔曼滤波算法在系统参数不确切已知或随时间变化时将无法直接应用。在区间分析的基础上,通过将不确定系统建成区间模型,在其他假设条件与标准卡尔曼滤波相同的前提下,分析了一种处理系统参数不确定性的区间卡尔曼滤波算法,并对其在参数估计方面的应用进行了探讨。

Kalman filtering algorithm can be used not only in state estimation, but also in online parameter estimation of dynamic system, especially in the time-varying parameter estimation. The traditional Kalman filtering algorithm can not be used directly when the system parameters are not precisely known or change with time. Based on the interval analysis, this paper analyzes a kind of interval Kalman filtering algorithm to deal with the uncertainty of system parameters under the precondition of other assumptive conditions being the same as that of standard Kalman filtering through establishing the interval model of the uncertainty system,and discusses its application into the parameter estimation.