Data-based control of Logical Networks

Abstract

In recent years, data-driven approaches have become increasingly pervasive across all areas of control engineering. However, the applications of data-based techniques to Boolean control networks (BCNs) are still very limited. In this paper we aim to fill this gap, by exploring the possibility of evaluating some basic features, i.e., reachability and equilibria, and of solving two fundamental control problems, i.e., safe control and output regulation, for a BCN, leveraging only a limited amount of data generated by the network, without knowing or identifying its model.

The paper is accepted for publication in Automatica