A general solution to the simultaneous stabilization problem by analytic interpolation

TL;DR

This paper introduces a unified analytic interpolation method for the simultaneous stabilization of multiple control systems, extending scalar results to multivariable cases and demonstrating effectiveness through numerical examples.

Contribution

It provides necessary and sufficient conditions for simultaneous stabilization, extending previous results with derivative constraints and a Riccati-based solution approach.

Findings

Unified method for scalar and multivariable stabilization

Extension of Ghosh's results with derivative constraints

Numerical examples demonstrating effectiveness

Abstract

In this paper, we tackle the significant challenge of simultaneous stabilization in control systems engineering, where the aim is to employ a single controller to ensure stability across multiple systems. We delve into both scalar and multivariable scenarios. For the scalar case, we present the necessary and sufficient conditions for a single controller to stabilize multiple plants and reformulate these conditions to interpolation constraints, which expand Ghosh's results by allowing derivative constraints. Furthermore, we implement a methodology based on a Riccati-type matrix equation, called the Covariance Extension Equation. This approach enables us to parameterize all potential solutions using a monic Schur polynomial. Consequently, we extend our result to the multivariable scenario and derive the necessary and sufficient conditions for a group of $m\times m$ plants to be simultaneously stabilizable, which can also be solved by our analytic interpolation method. Finally, we construct four numerical examples, showcasing the application of our method across various scenarios encountered in control systems engineering and highlighting its ability to stabilize diverse systems efficiently and reliably.