标题： 一种用于实时输入参数状态估计的无迹卡尔曼滤波方法 显示英文标题

标题： An unscented Kalman filter method for real time input-parameter-state estimation

摘要： 本文探讨了一种新型无迹卡尔曼滤波器在线性和非线性系统上的输入-参数-状态估计能力。 在每个时间步内，未知输入被分为两个阶段进行估计。 首先，预测的动态状态和系统参数提供输入的估计。 其次，与测量数据校正后的状态和参数提供最终估计。 重要的是，通过扰动分析证明，至少存在一个零或非零已知输入的系统可能被唯一识别。 这种仅输出的方法相比传统的仅输出参数识别策略，能够更好地理解系统，因为所有动态状态、参数和输入都是联合且实时估计的。 显示英文摘要

摘要： The input-parameter-state estimation capabilities of a novel unscented Kalman filter is examined herein on both linear and nonlinear systems. The unknown input is estimated in two stages within each time step. Firstly, the predicted dynamic states and the system parameters provide an estimation of the input. Secondly, the corrected with measurements states and parameters provide a final estimation. Importantly, it is demonstrated using the perturbation analysis that, a system with at least a zero or a non-zero known input can potentially be uniquely identified. This output-only methodology allows for a better understanding of the system compared to classical output-only parameter identification strategies, given that all the dynamic states, the parameters, and the input are estimated jointly and in real-time.