论文标题
稀疏感应和最佳精度：$ \ Mathcal {h} _2/\ Mathcal {h} _ {\ infty} $最佳观察者设计的集成框架
Sparse Sensing and Optimal Precision: An Integrated Framework for $\mathcal{H}_2/\mathcal{H}_{\infty}$ Optimal Observer Design
论文作者
论文摘要
在本文中，我们同时确定最佳传感器精度和观察者增益，从而达到了状态估计中指定的准确性。与未知的观察者增益一起，该配方参数化了与传感器噪声相对应的外源输入的缩放。此缩放的倒数定义为传感器的精度，并且通过最大程度地降低精度向量的$ L_1 $规范来实现稀疏度。优化是通过确保状态估计中指定准确性的约束来执行的，在状态估计中指定准确性，这些估计是根据$ \ Mathcal {H} _2 $或$ \ Mathcal {h} _ {\ infty} $规范的错误动力学。本文介绍的结果应用于F-16飞机的线性纵向模型。
In this paper, we simultaneously determine the optimal sensor precision and the observer gain, which achieves the specified accuracy in the state estimates. Along with the unknown observer gain, the formulation parameterizes the scaling of the exogenous inputs that correspond to the sensor noise. Reciprocal of this scaling is defined as the sensor precision, and sparseness is achieved by minimizing the $l_1$ norm of the precision vector. The optimization is performed with constraints guaranteeing specified accuracy in state estimates, which are defined in terms of $\mathcal{H}_2$ or $\mathcal{H}_{\infty}$ norms of the error dynamics. The results presented in this paper are applied to the linearized longitudinal model of an F-16 aircraft.
