论文标题
同时状态和参数估计：灵敏度分析的作用
Simultaneous state and parameter estimation: the role of sensitivity analysis
论文作者
论文摘要
状态和参数估计对于过程监视和控制至关重要。可观察性在状态和参数估计中都起着重要作用。在同时状态和参数估计中，通常将参数作为原始系统的额外状态增强。当可观察到增强系统时，可以使用各种现有的状态估计方法同时估算状态和参数。但是，当无法观察到增强系统时，我们应该如何最大程度地提取所测量输出中包含的信息。本文涉及当增强系统无法完全观察到的同时状态和参数估计。具体而言，我们首先显示灵敏度分析与动态系统的可观察性如何相关，然后说明如何使用它来选择变量进行同时估计。我们还提出了一个可以自然的方式使用变量选择的移动范围估计（MHE）设计。进行广泛的模拟以显示拟议方法的效率。
State and parameter estimation is essential for process monitoring and control. Observability plays an important role in both state and parameter estimation. In simultaneous state and parameter estimation, the parameters are often augmented as extra states of the original system. When the augmented system is observable, various existing state estimation approaches may be used to estimate the states and parameters simultaneously. However, when the augmented system is not observable, how we should proceed to maximally extract the information contained in the measured outputs is not clear. This paper concerns about simultaneous state and parameter estimation when the augmented system is not fully observable. Specifically, we first show how sensitivity analysis is related to observability of a dynamical system, and then illustrate how it may be used to select variables for simultaneous estimation. We also propose a moving horizon state estimation (MHE) design that can use the variable selection results in a natural way. Extensive simulations are carried out to show the efficiency of the proposed approach.
