Quantization of linear systems

Nicola Elia, Sanjoy K. Mitter

Research output: Contribution to journalConference articlepeer-review

33 Scopus citations


In this paper, we show that the coarsest quantizer that quadratically stabilizes a single input linear discrete time invariant system is logarithmic, and can be computed by solving a special LQR problem. We provide a closed form for the optimal logarithmic base exclusively in terms of the unstable eigenvalues of the system. We show how to design quantized state-feedback in general, and quantized state estimators in the case where all the eigenvalues of the system are unstable. This leads to the design of output feedback controllers with quantized measurements and controls. The theory is extended in various ways in the complete version of this paper available from the authors.

Original languageEnglish (US)
Pages (from-to)3428-3433
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - Dec 1 1999
Externally publishedYes
EventThe 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA
Duration: Dec 7 1999Dec 10 1999


Dive into the research topics of 'Quantization of linear systems'. Together they form a unique fingerprint.

Cite this