模型参数失配有界下的扩展集员估计方法

在非线性模型参数失配下,直接采用滤波算法很难获到理想的估计状态.本文基于扩展集员估计方法,在状态估计中引入参数的不确定信息,提出一种参数失配有界下的状态估计方法.该方法应用区间或集合运算的法则,计算由参数失配引起的偏差范围,并将其用椭球集外包.在状态估计的预测步,通过该偏差椭球集与先验椭球区间的并运算,得到预测椭球区间;在状态估计的更新步,利用观测椭球集对预测椭球区间进行更新,从而得到后验椭球集合以及状态估计值.最后,在数值仿真和发酵模型中的仿真应用验证了算法的有效性.

Extended set membership filtering method for process with bounded-mismatch parameters

Given a nonlinear model with mismatch parameters, it is difficult to obtain an accurate state estimation via thegeneral filtering methods. In this paper, based on the extended set membership estimation method, a novel state estimationmethod is proposed for the processes with bounded-mismatch parameters by introducing the uncertainty information ofparameter. In the proposed method, the deviation scope caused by the parameter mismatch is calculated by the intervaloperation and interval expansion functions, then it is enclosed by a ellipsoid set. In the prediction step of state estimation,the prediction ellipsoid is obtained by the summation of the parameter deviation ellipsoid set and the interval of the prioriellipsoid; In the update step, by using the observation ellipsoid set to update the priori ellipsoid, the posterior ellipsoidset and then the state estimate are derived. The applications in a numerical example and a fermenter process show theeffectiveness of the proposed method.