Dynamics and control of chemical process networks: Integrating physics, communication and computation

Abstract

This paper provides the theoretical foundation for the modeling, analysis and control of integrated chemical process networks, or, in short, “process networks.” The dynamics of process networks is represented using state-space descriptions derived from classical irreversible thermodynamics and constrained by the second law so that dissipation is always non-negative. The state descriptions (models) derived from this point of view provide exact process representations. A unique, quadratic Lyapunov function for stability analysis and control design is derived directly from the entropy. The resulting process models are complex and simplifications may be needed in practical applications. Time-scale decomposition and singular perturbation theory provide the basis for exploring the network-level dynamic behavior that emerges as a result of tight inventory integration, and developing appropriate reduced-order models and a hierarchy of control systems for managing inventories and inventory flows. Model-based networked control and Lyapunov theory are leveraged to develop an integrated control and communication strategy that manages the information flows between the network components and explicitly accounts for communication constraints.