Exploring Distributed Control Systems Through Scientometric Analysis: Control and Communication Insights

¹ Department of ECE, SR University, Warangal - 506371, Telangana, India
² Department of EEE, SR University, Warangal - 506371, Telangana, India
³ Center for Informetrics and statistics, SR University, Warangal - 506371, Telangana, India

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Published online: 26 June 2026

Abstract

Decentralized Control Systems (DCS) are an important part of today's industrial automation, smart grid and cyber-physical systems, as they allow for decentralized decision-making, scalability and operational resilience based on a robust communication infrastructures. Geographically distributed controllers, field devices and human–machine interfaces provide added flexibility, reliability and adaptability for complex industrial environments. New challenges with com-munication latencies, interoperability limitations, and cybersecurity vulnerabili-ties continue to arise due to the quickly evolving technologies and the increasing adoption of enabling technologies such as the Internet of Things (IoT), digital twins, and reinforcement learning based control strategies. Also, there is little in-depth scientometric knowledge about the trends, thematic development, and col-laboration of the international research landscape in DCS research. This study aims to deliver a twofold insight by giving not only a technical overview about the new DCS paradigms, but also a scientometric analysis of the publications on DCS research from the year 2015 to 2025. From the perspective of electronics and control systems, the analysis describes the development of distributed con-trol architectures, industrial control strategies, and communication reliability mechanisms that enable today's industrial automation and cyber-physical sys-tems. The scientometric mapping techniques were applied to a dataset compris-ing about 340 publications in 153 sources, related to keyword co-occurrence, citation structure, trend in publications, and international and institutional col-laboration network. These findings showed an annual growth rate for publica-tions of −8.86%, and an average of 7.126 citations per publication. The major research areas are: IoT-equipped SCADA systems, cyber security frameworks, adaptive consensus protocols and artificial intelligence-based control solutions. The findings presented here provide important insights into the intellectual struc-ture of DCS research and help in the design of secure, scalable and intelligent automation systems in practice.