Systematic Transformation of Chemical Catalyst Models for Control Design

Abstract

Common system analysis and controller design methods are based on state-space models. However, most physical-chemical catalyst models are not represented in a state-space. In this paper, we present an approach to transform simplified physical–chemical models into the state-space, and hereby, we introduce the concept of weighting functions. The weighting functions represent the catalyst model in a compact form and are a convenient way for system analysis. The weighting functions will be analyzed from the system theoretical and chemical point of view. The generalization of this approach will be demonstrated. Exemplarily, three reaction mechanisms will be transformed into nonlinear state-space models. Based on the first model, the nonlinear state-space model will be linearized and a linear quadratic controller will be designed. Contrarily to the LQ controllers in the literature, the weighting matrix for the state vector is chosen in the model-based form. The only few design parameters are intuitive to choose.