Abstract
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 ω-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 ω-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.
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Index Terms
A theory of robust omega-regular software synthesis
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