Symbolic Models for Infinite Networks of Control Systems: A Compositional Approach
Siyuan Liu, Navid Noroozi, Majid Zamani

TL;DR
This paper introduces a compositional method for creating symbolic models of infinite networks of control systems, ensuring guaranteed output behavior bounds and enabling decentralized safety controller synthesis.
Contribution
It develops a novel compositional framework using alternating simulation functions for infinite networks, allowing scalable symbolic model construction with guaranteed accuracy.
Findings
Successfully applied to a road traffic network with infinitely many cells.
Provides a systematic algorithm for local symbolic model construction.
Enables decentralized safety control synthesis for infinite networks.
Abstract
This paper presents a compositional framework for the construction of symbolic models for a network composed of a countably infinite number of finite-dimensional discrete-time control subsystems. We refer to such a network as infinite network. The proposed approach is based on the notion of alternating simulation functions. This notion relates a concrete network to its symbolic model with guaranteed mismatch bounds between their output behaviors. We propose a compositional approach to construct a symbolic model for an infinite network, together with an alternating simulation function, by composing symbolic models and alternating simulation functions constructed for subsystems. Assuming that each subsystem is incrementally input-to-state stable and under some small-gain type conditions, we present an algorithm for orderly constructing local symbolic models with properly designed…
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