SYSYMar 4, 2018

Robust Abstractions for Control Synthesis: Robustness Equals Realizability for Linear-Time Properties

arXiv:1803.013871.222 citationsh-index: 101
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For control theorists and engineers, this work provides a theoretical foundation and algorithmic approach to synthesizing provably correct controllers for nonlinear systems under uncertainty, addressing a key bottleneck in abstraction-based control synthesis.

This paper defines robust abstractions for uncertain transition systems and shows they preserve robust satisfaction of linear-time properties. It provides computational procedures to construct both sound and approximately complete robust abstractions for general nonlinear control systems, proving that robust control synthesis for such systems is robustly decidable.

We define robust abstractions for synthesizing provably correct and robust controllers for (possibly infinite) uncertain transition systems. It is shown that robust abstractions are sound in the sense that they preserve robust satisfaction of linear-time properties. We then focus on discrete-time control systems modelled by nonlinear difference equations with inputs and define concrete robust abstractions for them. While most abstraction techniques in the literature for nonlinear systems focus on constructing sound abstractions, we present computational procedures for constructing both sound and approximately complete robust abstractions for general nonlinear control systems without stability assumptions. Such procedures are approximately complete in the sense that, given a concrete discrete-time control system and an arbitrarily small perturbation of this system, there exists a finite transition system that robustly abstracts the concrete system and is abstracted by the slightly perturbed system simultaneously. A direct consequence of this result is that robust control synthesis for discrete-time nonlinear systems and linear-time specifications is robustly decidable. More specifically, if there exists a robust control strategy that realizes a given linear-time specification, we can algorithmically construct a (potentially less) robust control strategy that realizes the same specification. The theoretical results are illustrated with a simple motion planning example.

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