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

Content Provider	IEEE Xplore Digital Library
Author	Sze Zheng Yong Minghui Zhu Frazzoli, E.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA (Minghui Zhu) \|\| Lab. for Inf. & Decision Syst., Massachusetts Inst. of Technol., Cambridge, MA, USA (Sze Zheng Yong; Frazzoli, E.)
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.
Starting Page	2511
Ending Page	2518
File Size	501016
Page Count	8
File Format	PDF
e-ISBN	9781479986842
DOI	10.1109/ACC.2015.7171109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Noise Noise measurement Approximation methods Covariance matrices State estimation Stochastic systems
Content Type	Text
Resource Type	Article

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