Robust Causal Transform Coding for LQG Systems with Delay Loss in Communications

Mohammad Kazem Izadinasab, Amir Homayoun Bahari Sani, Farshad Lahouti, Babak Hassibi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


A networked controlled system (NCS) in which the plant communicates to the controller over a channel with random delay loss is considered. The channel model is motivated by recent development of tree codes for NCS, which effectively translates an erasure channel to one with random delay. A causal transform coding scheme is presented which exploits the plant state memory for efficient communications (compression) and provides robustness to channel delay loss. In this setting, we analyze the performance of linear quadratic Gaussian (LQG) closed-loop systems and the design of the optimal controller. The design of the transform code for LQG systems is posed as a channel optimized source coding problem of minimizing a weighted mean squared error over the channel. The solution is characterized in two steps of obtaining the optimized causal encoding and decoding transforms and rate allocation across a set of transform coding quantizers. Numerical and simulation results for Gauss-Markov sources and an LQG system demonstrate the effectiveness of the proposed schemes.
Original languageEnglish (US)
Title of host publication2016 American Control Conference (ACC)
Number of pages6
ISBN (Print)9781467386821
StatePublished - 2016
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-23
Acknowledgements: This work was supported in part by the National Science Foundation under grants CCF-1423663 and CCF-1409204, by a grant from Qualcomm Inc., by NASA's Jet Propulsion Laboratory through the President and Director's Fund, and by King Abdullah University of Science and Technology.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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