Robust Decentralized Stabilization of Markovian Jump Large-Scale Systems: A Neighboring Mode Dependent Control Approach

TL;DR

This paper develops a decentralized control method for large-scale systems with Markovian jumps, using neighboring mode information to ensure stability despite uncertainties.

Contribution

It introduces a novel stabilization approach based on rank-constrained LMIs that leverages local and neighboring mode data for large-scale Markovian systems.

Findings

Sufficient conditions for stabilization are derived.

The method is validated through a numerical example.

The approach enhances robustness in decentralized control.

Abstract

This paper is concerned with the decentralized stabilization problem for a class of uncertain large-scale systems with Markovian jump parameters. The controllers use local subsystem states and neighboring mode information to generate local control inputs. A sufficient condition involving rank constrained linear matrix inequalities is proposed for the design of such controllers. A numerical example is given to illustrate the developed theory.