Seongmin Heo

Dynamics and control of high duty counter-current heat exchangers

In this paper, we analyze a class of high duty counter-current heat exchangers. A high duty counter-current heat exchanger is modeled by two first order stiff PDEs, which show a potential of multi-time scale dynamics. Using singular perturbations, a non-stiff reduced model capturing the slow time scale dynamics is derived. Input/output linearizing controllers are derived based on both the full model and the reduced model, and the advantages of using the controller based on the reduced model are documented via simulations.

Graph reduction for hierarchical control of energy integrated process networks

In this paper, we propose a graph-theoretic algorithm that can be used to analyze complex chemical processes comprising of multiple energy integration loops. Such networks are known to exhibit dynamics in multiple time scales. The algorithm uses information on the order of magnitude of the different energy flows and determines automatically the time scales where the units evolve, the manipulated inputs acting in the different time scales and the form of the reduced order models in each time scale. The application of the algorithm is illustrated through a case study of a benchmark chemical process.

Time scale decomposition in complex reaction systems: A graph theoretic analysis

Abstract The formulation of a kinetic model for a complex reaction network typically yields reaction rates which vary over orders of magnitude. This results in time scale separation that makes the model inherently stiff. In this work, a graph-theoretic framework is developed for time scale decomposition of complex reaction networks to separate the slow and fast time scales, and to identify pseudo-species that evolve only in the slow time scale. The reaction network is represented using a directed bi-partite graph and cycles that correspond to closed walks are used to identify interactions between species participating in fast/equilibrated reactions. Subsequently, an algorithm which connects the cycles to form the pseudo-species is utilized to eliminate the fast rate terms. These pseudo-species are used to formulate reduced, non-stiff kinetic models of the reaction system. Two reaction systems are considered to show the efficacy of this framework in the context of thermochemical and biochemical processing.

Input/output hierarchical clustering in process networks based on relative degrees

In this paper, a divisive hierarchical clustering method is proposed to address the problem of pairing of manipulated inputs and controlled outputs. Specifically, an integer nonlinear optimization problem is formulated to identify groups of inputs and outputs with strong structural coupling quantified by relative degrees. This optimization problem can be solved in a hierarchical manner to generate a hierarchy of block decentralized control configurations. The application of the method is illustrated through a case study on an example chemical process network.

Control structure design for complex energy integrated networks using graph-theoretic methods

In this paper, we propose a mixed integer program (MIP) formulation which can be used to synthesize multi-loop hierarchical control structures for tightly energy integrated plants, which are known to exhibit multiple-time scale energy dynamics. First, we represent the network as an energy flow graph, and perform graph reduction using graph-theoretic algorithms that we have previously developed, to analyze the time scale properties of the network and obtain energy flow subgraphs for each time scale. Then, from each energy flow subgraph, we construct an equation graph from which we can extract relative degree information. Using the proposed MIP, optimal input/output pairing sets are obtained, which minimize the structural coupling in each time scale. We illustrate the application of the proposed work through a case study of a benchmark chemical process.