Predictive control design subject to multiple missing measurements

This paper investigates the problem of predictive control for control systems with multiple missing measurements. An extended stochastic model is introduced to describe and compensate missing data. The state feedback control scheme is designed to minimize an upper bound on the expected value of an i...

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Bibliographic Details
Published in2012 10th World Congress on Intelligent Control and Automation (WCICA pp. 2701 - 2705
Main Authors Yuanyuan Zou, Yugang Niu
Format Conference Proceeding
LanguageChinese
English
Published IEEE 01.07.2012
Subjects
Closed loop systems
Loss measurement
missing data
Optimization
Predictive control
State feedback
Stochastic processes
stochastic stability
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ISBN9781467313971
1467313971
DOI10.1109/WCICA.2012.6358330

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Summary:This paper investigates the problem of predictive control for control systems with multiple missing measurements. An extended stochastic model is introduced to describe and compensate missing data. The state feedback control scheme is designed to minimize an upper bound on the expected value of an infinite horizon quadratic performance objective at each sampling instant. It is shown that the present scheme can guarantee the stochastic stability of the closed-loop system.
ISBN:9781467313971
1467313971
DOI:10.1109/WCICA.2012.6358330