Control Model Development for Packed Bed Chemical Reactors

Abstract

Although control algorithms have been conceived for industrial chemical systems, their acceptance by industry has been slow due to a lack of direct experimental evidence of their effectiveness and to volumes of conflicting, or at least incompatible, recommendations on control structure design. This thesis provides the basis for a concerted theoretical and experimental program in multivariable process control structure design for packed bed chemical reactors by presenting an in-depth control analysis of a practical, multivariable, distributed parameter system-the heat conduction problem defined by the simple diffusion equation-using both frequency-domain and time-domain analyses and the formulation, numerical solution, and analysis of a detailed model for packed bed reactors, along with reduction to a low-order state-space representation suitable for on-line process control. The study of the heat conduction system allowed for consideration of various control design techniques and the relation between measurement structure and control system design. This study shows that the choice of measurements and their locations significantly affects the optimal control design and the usefulness of the different design techniques and the importance of an accurate process model and the necessity of model reduction to a low-order state-space representation for control structure design and implementation. The second portion of this study provides a detailed mathematical modeling analysis of packed bed catalytic reactors that significantly extends previous studies in the detail of the model and in the consideration of all aspects of the model development and reduction to a state-space control representation. The general view that modeling simplifications are desired since they lead to a reduction in numerical solution effort is contested, and it is shown that many simplifications are no longer necessary with today's advanced computational capabilities. A unified approach to dynamic reactor modeling is developed and its importance in the accurate description of dynamic and steady state reactor behavior, in the investigation of reactor start-up or the effects of process disturbances, and in the development of an accurate reduced state-space model for the design of control structures to stabilize the reactor under various disturbances or to provide optimal system recovery from input changes is shown.