UC Davis

Modern industrial plants have become increasingly dependent on networked control system architectures in which dedicated sensor‐controller, controller‐actuator, and controller-controller links are replaced by real-time shared (wired or wireless) digital communication networks that operate over specialized industrial networks and protocols. While networked control systems offer a multitude of economic and operational benefits, the increased reliance on shared communication networks comes with a host of fundamental challenges that need to be addressed. For example, challenges such as network resource constraints, data losses, communication delays and real-time scheduling constraints are tied to the inherent limitations on the transmission and processing capabilities of the communication medium, and if left unaddressed can cause operational instabilities or closed-loop performance deterioration. These challenges have motivated a significant and growing body of research work on the analysis and design of networked control systems. An approach that has been proposed to address a number of these challenges is the use of model-based control, however, a central problem that has yet to be addressed is the robustness of the control system to plant-model mismatches that could arise due to things like fouling in heat-exchanger systems or deactivation of catalysts in catalytic reactors.

Motivated by these considerations, this dissertation aims to develop an identification-integrated model-based control framework that enhances the performance and security of networked control systems, and address framework implementation issues such as communication resource constraints, lack of full state measurements, distributed systems, communication strategies, nonlinearities, and measurement errors. Finally, the implementation and effectiveness of the developed framework through simulated chemical process examples.