Minimum jointly structural input and output selection for strongly connected networks

TL;DR

This paper addresses the problem of determining the minimum number of state variables to actuate and measure in strongly connected networks to ensure controllability and observability, providing a polynomial-time solution.

Contribution

It introduces a polynomial-time method to jointly optimize input and output selection for structural controllability and observability in strongly connected networks.

Findings

Polynomial-time solution for joint input-output selection

Optimal number of actuated and measured variables identified

Applicable to multi-agent system design constraints

Abstract

In this paper, given a linear time-invariant strongly connected network, we study the problem of determining the minimum number of state variables that need to be simultaneously actuated and measured to ensure structural controllability and observability, respectively. This problem is fundamental in the design of multi-agent systems, where there are economic constraints in the decision of which agents to equip with a more costly on-board system that will allow the agent to have both actuation and sensing capabilities. Despite the combinatorial nature of this problem, we present a solution that couples the design of both structural controllability and structural observability counterparts to address it with polynomial-time complexity.