Finite horizon robust Kalman filter design

Minyue Fu; Carlos E. de Souza; Zhi Quan Luo

Finite horizon robust Kalman filter design

Minyue Fu, Carlos E. de Souza, Zhi Quan Luo

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

16 Scopus citations

Abstract

In this paper, we study the problem of finite horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters which can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. Also proposed is a recursive design method which can be applied to real-time applications.

Original language	English (US)
Pages (from-to)	4555-4560
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	5
State	Published - Dec 1 1999
Event	The 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA Duration: Dec 7 1999 → Dec 10 1999

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title = "Finite horizon robust Kalman filter design",

abstract = "In this paper, we study the problem of finite horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters which can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. Also proposed is a recursive design method which can be applied to real-time applications.",

author = "Minyue Fu and {de Souza}, {Carlos E.} and Luo, {Zhi Quan}",

year = "1999",

month = dec,

day = "1",

language = "English (US)",

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journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

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note = "The 38th IEEE Conference on Decision and Control (CDC) ; Conference date: 07-12-1999 Through 10-12-1999",

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T1 - Finite horizon robust Kalman filter design

AU - Fu, Minyue

AU - de Souza, Carlos E.

AU - Luo, Zhi Quan

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N2 - In this paper, we study the problem of finite horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters which can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. Also proposed is a recursive design method which can be applied to real-time applications.

AB - In this paper, we study the problem of finite horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters which can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. Also proposed is a recursive design method which can be applied to real-time applications.

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M3 - Conference article

AN - SCOPUS:0033349764

VL - 5

SP - 4555

EP - 4560

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

SN - 0191-2216

T2 - The 38th IEEE Conference on Decision and Control (CDC)

Y2 - 7 December 1999 through 10 December 1999

ER -

Finite horizon robust Kalman filter design

Abstract

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