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Stabilizability of Stochastic Linear Systems with Finite Feedback Data Rates

Nair, Girish N., Evans, Robin J.·2004·SIAM Journal on Control and Optimization

Abstract

Feedback control with limited data rates is an emerging area which incorporates ideas from both control and information theory. A fundamental question it poses is how low the closed-loop data rate can be made before a given dynamical system is impossible to stabilize by any coding and control law. Analogously to source coding, this defines the smallest error-free data rate sufficient to achieve "reliable" control, and explicit expressions for it have been derived for linear time-invariant systems without disturbances. In this paper, the more general case of finite-dimensional linear systems with process and observation noise is considered, the object being mean square state stability. By inductive arguments employing the entropy power inequality of information theory, and a new quantizer error bound, an explicit expression for the infimum stabilizing data rate is derived, under very mild conditions on the initial state and noise probability distributions.

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Metadata

Authors
Nair, G. N., & Evans, R. J.
Venue
SIAM Journal on Control and Optimization
Published
2004-01
Volume
43
Issue
2
Pages
413-436
ISSN
  • 0363-0129 (ISSN-L)
  • 1095-7138
OpenAlex
W1978848993
Cited by
720
References
14
FWCI
65.66
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Stabilizability of Stochastic Linear Systems with Finite Feedback Data Rates. https://app.cochat.ai/papers/10.1137/s0363012902402116
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Nair, G. N., & Evans, R. J. (2004). Stabilizability of Stochastic Linear Systems with Finite Feedback Data Rates. SIAM Journal on Control and Optimization. https://doi.org/10.1137/s0363012902402116

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