A Mean-square Analysis and Design Framework for Networked Control: Correlated Stochastic Multiplicative Uncertainties

Project: Research

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The goal of this project is to develop basic theory of networked control aiming at its practical application. Networked control, with today’s omnipresent and ever-expanding IT technology and infrastructure, is widely believed to be a key enabling and transformative technology for the next-generation engineering systems. Notable applications include, e.g., industrial control systems, manufacturing systems, intelligent transportation, distributed sensor networks, and more broadly, cyber physical systems and Internet of Things. Networked control systems differ from conventional feedback systems, in which communication noises and transmission losses usher in new challenges. This project targets a fundamental limitation with the current model and theory of networked control, that is, the communication channel noises must be independent or uncorrelated. This restriction limits severely its applicability; indeed, it poses a central obstacle for real-world applications, to, e.g., industrial control systems. We aim to develop a theoretical as well as a computational framework that focuses on networked systems with communication channels subject to correlated noises and transmission losses, which encompass a wide range of channel models and will be tackled as correlated stochastic multiplicative uncertainties. Central to our investigation are a set of synergistic objectives unified under this framework, including (1) developing a generalized mean-square small gain theorem capable of coping with correlated stochastic uncertainties; (2) developing mean-square stabilization conditions and optimal control methods under the generalized mean-square framework; (3) developing mean-square stability and stabilization conditions for systems containing random communication delays, and computational algorithms and analytical bounds for random jitter control. Throughout the execution of this project, the benchmark Tennessee Eastman process will be employed to guide and validate the theoretical development.  A coherent technical approach has been carved out to achieve the objectives, which is centered at the generalized mean-square small gain framework built on the correlated stochastic multiplicative uncertainty formulation. The framework attempts to overcome some of the existing limitations and restrictions, by presenting a considerably more realistic-in fact a generic-networked control model, and by developing theoretical results and computational algorithms to facilitate the practical applications of the networked control theory. The project is motivated by real-world industrial control systems, and it seeks to provide answers and solutions to the challenges for realistic applications to such systems. We hold the viewpoint that the understanding generated from this project will contribute significantly to the advance and application of the networked control theory, and more broadly, shed light into related fields such as cyber physical systems. 


Project number9042956
Grant typeGRF
Effective start/end date1/01/21 → …