A $\mu$-Analysis and Synthesis Framework for Partial Integral Equations using IQCs

TL;DR

This paper introduces a novel $mbda$-analysis and synthesis framework for infinite-dimensional systems using IQCs, enabling robust stability and performance analysis with reduced conservatism and practical computational tools.

Contribution

It develops a new framework connecting IQC multipliers with $mbda$-theory for partial integral equations, with implementation in PIETOOLS for practical analysis.

Findings

Significant reduction in conservatism over unstructured methods

Validated on Partial and Delay Differential Equations

Provides systematic stability-performance trade-off analysis

Abstract

We develop a $\mu$-analysis and synthesis framework for infinite-dimensional systems that leverages the Integral Quadratic Constraints (IQCs) to compute the structured singular value's upper bound. The methodology formulates robust stability and performance conditions jointly as Linear Partial Integral Inequalities within the Partial Integral Equation framework, establishing connections between IQC multipliers and $\mu$-theory. Computational implementation via PIETOOLS enables computational tools that practically applicable to spatially distributed infinite dimensional systems. Illustrations with the help of Partial and Delay Differential Equations validate the effectiveness of the framework, showing a significant reduction in conservatism compared to unstructured methods and providing systematic tools for stability-performance trade-off analysis.