Estimation of Strong Structural Controllable Subspace of Network: Equitable Partition Method

TL;DR

This paper introduces an equitable partition method to analyze the strong structural controllability of networks, providing bounds and invariants that enhance understanding of controllability in complex systems.

Contribution

It proposes a unified equitable partition approach to estimate the strong structural controllable subspace across various network scenarios, advancing controllability analysis methods.

Findings

Upper bounds for controllable subspace in different scenarios

Analysis of strong structural observability via dual system characteristics

Identification of invariant attributes in controllability analysis

Abstract

In this paper, the strong structural controllability of the network is analyzed. Based on the unified definition of equitable partition for kinds of scene, the upper bound of the strong structural controllable subspace in different scenarios is given, and the strong structural observability is analyzed by using the characteristics of the dual system. Finally, the practical significance when the dimension of the strong structural controllable subspace is less than the number of individuals is given, and an invariant attribute of strong structural controllability analysis is proposed.