Matrix-Valued Passivity Indices: Foundations, Properties, and Stability Implications

TL;DR

This paper introduces matrix-valued passivity indices for MIMO systems, generalizing classical scalar indices to better capture system passivity, leading to improved stability analysis and control design.

Contribution

It extends scalar passivity indices to a matrix framework, revealing geometric properties and providing criteria for selecting representative matrices in MIMO systems.

Findings

Matrix-valued indices capture passivity coupling in MIMO systems.

The framework generalizes classical passivity results.

Enhanced stability assessment with less conservatism.

Abstract

The passivity index, a quantitative measure of a system's passivity deficiency or excess, has been widely used in stability analysis and control. Existing studies mostly rely on scalar forms of indices, which are restrictive for multi-input, multi-output (MIMO) systems. This paper extends the classical scalar indices to a systematic matrix-valued framework, referred to as passivity matrices. A broad range of classical results in passivity theory can be naturally generalized in this framework. We first show that, under the matrix representation, passivity indices essentially correspond to the curvature of the dissipativity functional under a second-variation interpretation. This result reveals that the intrinsic geometric structure of passivity consists of its directions and intensities, which a scalar index cannot fully capture. For linear time-invariant (LTI) systems, we examine the structural properties of passivity matrices with respect to the Loewner partial order and propose two principled criteria for selecting representative matrices. Compared with conventional scalar indices, the matrix-valued indices capture the passivity coupling among different input-output channels in MIMO systems and provide a more comprehensive description of system passivity. This richer information leads to lower passivation effort and less conservative stability assessment.