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Distribution-Free Mode-Estimators for a Class of Discrete-Time Jump-Linear Systems

机译:一类离散时间跳跃线性系统的无分布模式估计器

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This paper is concerned with the development of recursive distribution-free mode-estimators for a class of discrete-time jump-linear systems. The cornerstone of the proposed filters consists of an algebraic manipulation of the dynamics equation of the continuous state. This equation turns out to be linear with respect to the mode vector, and, under the assumption of perfect state information, provides a linear observation equation for the mode. Appending this equation to the known linear dynamics equation of the mode yields a linear non-Gaussian state-space model. A first mode-estimator is then derived using standard Linear Filtering results. A second filter is developed as an application of a general discrete-time filter, which approximates the continuous-time optimal non-linear filter (the conditional mean estimator for continuous time) for small sample times. The second filter is preferred from a performance point of view. Model order reduction is applied in order to avoid singularity issues in the filters implementations. The second filter is envisioned as a useful tool in the analysis and design of dual controllers for this type of hybrid systems.
机译:本文涉及一类离散时间跳跃线性系统的递归无分布模式估计器的开发。所提出的滤波器的基石由连续状态动力学方程的代数运算组成。相对于模式向量,该方程式是线性的,并且在理想状态信息的假设下,提供了模式的线性观测方程式。将该方程附加到该模式的已知线性动力学方程,可以得出线性非高斯状态空间模型。然后使用标准线性滤波结果得出第一模式估计器。开发了第二个滤波器,作为通用离散时间滤波器的应用,它可以在较小的采样时间内近似连续时间最佳非线性滤波器(连续时间的条件均值估计器)。从性能的观点来看,第二过滤器是优选的。应用模型阶数减少是为了避免过滤器实现中出现奇点问题。可以预想第二个过滤器将成为分析和设计此类混合系统双控制器的有用工具。

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