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

Cite this

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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}",

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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

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VL - 5

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EP - 4560

JO - Proceedings of the IEEE Conference on Decision and Control

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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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