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A theory of robust omega-regular software synthesis

A theory of robust omega-regular software synthesis A Theory of Robust Omega-Regular Software Synthesis RUPAK MAJUMDAR, Max Planck Institute for Software Systems and University of California, Los Angeles ELAINE RENDER and PAULO TABUADA, University of California, Los Angeles A key property for systems subject to uncertainty in their operating environment is robustness: ensuring that unmodeled but bounded disturbances have only a proportionally bounded effect upon the behaviors of the system. Inspired by ideas from robust control and dissipative systems theory, we present a formal definition of robustness as well as algorithmic tools for the design of optimally robust controllers for -regular properties on discrete transition systems. Formally, we define metric automata--automata equipped with a metric on states--and strategies on metric automata which guarantee robustness for -regular properties. We present fixed-point algorithms to construct optimally robust strategies in polynomial time. In contrast to strategies computed by classical graph theoretic approaches, the strategies computed by our algorithm ensure that the behaviors of the controlled system gracefully degrade under the action of disturbances; the degree of degradation is parameterized by the magnitude of the disturbance. We show an application of our theory to the design of controllers that tolerate infinitely many transient errors provided they occur infrequently enough. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Embedded Computing Systems (TECS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2013 by ACM Inc.
ISSN
1539-9087
DOI
10.1145/2539036.2539044
Publisher site
See Article on Publisher Site

Abstract

A Theory of Robust Omega-Regular Software Synthesis RUPAK MAJUMDAR, Max Planck Institute for Software Systems and University of California, Los Angeles ELAINE RENDER and PAULO TABUADA, University of California, Los Angeles A key property for systems subject to uncertainty in their operating environment is robustness: ensuring that unmodeled but bounded disturbances have only a proportionally bounded effect upon the behaviors of the system. Inspired by ideas from robust control and dissipative systems theory, we present a formal definition of robustness as well as algorithmic tools for the design of optimally robust controllers for -regular properties on discrete transition systems. Formally, we define metric automata--automata equipped with a metric on states--and strategies on metric automata which guarantee robustness for -regular properties. We present fixed-point algorithms to construct optimally robust strategies in polynomial time. In contrast to strategies computed by classical graph theoretic approaches, the strategies computed by our algorithm ensure that the behaviors of the controlled system gracefully degrade under the action of disturbances; the degree of degradation is parameterized by the magnitude of the disturbance. We show an application of our theory to the design of controllers that tolerate infinitely many transient errors provided they occur infrequently enough.

Journal

ACM Transactions on Embedded Computing Systems (TECS)Association for Computing Machinery

Published: Dec 1, 2013

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