Simultaneous input and state estimation for linear time-invariant continuous-time stochastic systems with unknown inputs

Sze Yong, Minghui Zhu, Emilio Frazzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, we present an optimal filter for linear time-invariant continuous-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense. The optimality of the proposed filter is proven by reduction to an equivalent system without unknown inputs. Then, a second proof is given for a special case by limiting case approximations of the optimal discrete-time filter [1], thus establishing the connection between the continuous- and discrete-time filters. Conditions for the existence of a steady-state solution for the proposed filter are also given. Moreover, we show that a principle of separation of estimation and control holds for linear systems with unknown inputs. An example is given to demonstrate these claims.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2511-2518
Number of pages8
Volume2015-July
ISBN (Electronic)9781479986842
DOIs
StatePublished - Jan 1 2015
Externally publishedYes
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Other

Other2015 American Control Conference, ACC 2015
CountryUnited States
CityChicago
Period7/1/157/3/15

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Yong, S., Zhu, M., & Frazzoli, E. (2015). Simultaneous input and state estimation for linear time-invariant continuous-time stochastic systems with unknown inputs. In ACC 2015 - 2015 American Control Conference (Vol. 2015-July, pp. 2511-2518). [7171109] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2015.7171109