模型参数失配有界下的扩展集员估计方法
发布时间：2019-05-24 03:33
【摘要】：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.
[Abstract]:Under the condition of parameter mismatch of nonlinear model, it is difficult to obtain the ideal estimation state by using filtering algorithm directly. In this paper, based on the extended set member estimation method, the uncertain information of parameters is introduced into the state estimation, and a state estimation method with parameter mismatch bound is proposed. In this method, the algorithm of interval or set operation is used to calculate the deviation range caused by parameter mismatch, and the ellipsoid set is used to outsource it. In the prediction step of state estimation, the prediction ellipsoid interval is obtained by the union operation between the deviated ellipsoid set and the prior ellipsoid interval. In the updating step of state estimation, the prediction ellipsoid interval is updated by using the observed ellipsoid set, and the posterior ellipsoid set and the state estimation value are obtained. Finally, the effectiveness of the algorithm is verified by the simulation applications in numerical simulation and fermentation model.
【作者单位】： 江南大学轻工过程先进控制教育部重点实验室;
【基金】：国家自然科学基金项目(61573169)资助~~
【分类号】：TP301.6
[Abstract]:Under the condition of parameter mismatch of nonlinear model, it is difficult to obtain the ideal estimation state by using filtering algorithm directly. In this paper, based on the extended set member estimation method, the uncertain information of parameters is introduced into the state estimation, and a state estimation method with parameter mismatch bound is proposed. In this method, the algorithm of interval or set operation is used to calculate the deviation range caused by parameter mismatch, and the ellipsoid set is used to outsource it. In the prediction step of state estimation, the prediction ellipsoid interval is obtained by the union operation between the deviated ellipsoid set and the prior ellipsoid interval. In the updating step of state estimation, the prediction ellipsoid interval is updated by using the observed ellipsoid set, and the posterior ellipsoid set and the state estimation value are obtained. Finally, the effectiveness of the algorithm is verified by the simulation applications in numerical simulation and fermentation model.
【作者单位】： 江南大学轻工过程先进控制教育部重点实验室;
【基金】：国家自然科学基金项目(61573169)资助~~
【分类号】：TP301.6
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