Abstract
In this paper, we present a unified optimal and exponentially stable filter for linear discrete-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense, without making any assumptions on the direct feedthrough matrix. We also provide the connection between the stability of the estimator and a system property known as strong detectability, and discuss the global optimality of the proposed filter. Finally, an illustrative example is given to demonstrate the performance of the unified unbiased minimum-variance filter.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 321-329 |
| Number of pages | 9 |
| Journal | Automatica |
| Volume | 63 |
| DOIs | |
| State | Published - Jan 1 2016 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Electrical and Electronic Engineering
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Yong, S. Z., Zhu, M., & Frazzoli, E. (2016). A unified filter for simultaneous input and state estimation of linear discrete-time stochastic systems. Automatica, 63, 321-329. https://doi.org/10.1016/j.automatica.2015.10.040