Bayesian design of experiments for nonlinear dynamic system identification
Bayesian design of experiments for nonlinear dynamic system identification
复制标题
非线性动态系统辨识的贝叶斯实验设计
DOI：
10.5555/2263019.2263030
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Susanne Zaglauer
中科院分区：
文献类型：
--
作者：
Susanne Zaglauer
D-最优和其他基于模型的实验设计，如委员会标准查询，经常受到批评，因为它们依赖于统计模型，并且缺乏对假设模型中已识别的不规则性的明确分配。此外，D-最优实验设计倾向于显著地加权实验空间的边界区域。在极端情况下，实验空间的边界点是实验候选点。为了化解这一批评，一个新的在线贝叶斯设计的非线性动态系统的识别，这是服务的灵活性，同时更能抵抗模型所造成的偏见。这种方法的一个优点也是小的修改的D-最优设计，以增加独立的D-最优设计所选择的模型approach.This贡献，包括介绍不同的方法的实验设计的非线性动态系统识别。因此，无模型和基于模型的实验设计的介绍和新的在线贝叶斯设计的非线性动态系统的识别。所提出的设计方案是适当的，以确定内燃机的动力学，可用于识别参数的分析和仿真模型，并通过仿真进行评估。
D-optimal and other model-based experimental designs, like the Query by Committee criterion, are often criticised because of their dependency to the statistical model and the lack of the explicit allocation of the identified irregularities of the assumed model. Furthermore, D-optimal experimental designs tend to weight the boundary area of the experimental space significantly. In extreme cases the boundary points of the experimental space are the experimental candidates. In order to defuse this critique a new online Bayesian design for the nonlinear dynamic system identification is introduced, which serves the flexibility and which is concurrently more resistant against the bias caused by the model. An advantage of this approach is also the small modification of the D-optimal design to increase the independency of the D-optimal design to the chosen model approach.This contribution includes the presentation of different methods for the Design of Experiments for nonlinear dynamic system identification. Therefore, model-free and model-based based experimental designs are introduced and the new online Bayesian design for nonlinear dynamic system identification is represented. The presented design plans are appropriate to identify the dynamics of combustion engines, can be used to identify the parameters of both analytical and simulation models and are evaluated by simulations.