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|Type:||Artigo de periódico|
|Title:||Controle Avançado Utilizando Dmc E Simulação Termodinâmica|
|Abstract:||Exothermic behavior is commonly faced on advanced process control projects. For lower degrees of exothermic, linear controllers can be adapted by various means to overcome the changes in process gain apparent in these types of process. However, processes where the effect of a disturbance can change the gain direction, depending on reactor-feed concentrations and temperature, present a special challenge for advanced process control projects. In a few of these cases, if one can force the process to remain in an area of consistent disturbance behavior, one can usually safely use the linear controller. However, if one must operate the process in areas where the disturbance effects do change direction, a nonlinear controller is generally advised. This paper demonstrates that for one subset of exothermic processes, a linear controller can also be successfully used. This subset consists of processes with thermodynamically simple fluids (i.e., non-polymeric and non-electrolytic) and a few independent variables. This strategy of using a linear controller on an exothermic process displaying this sort of disturbance effect is justified. In this plant there is already a large installed base of linear controllers at the plant site without an existing base of nonlinear controllers and the new controller is going to be a sub-controller inside a greater linear controller. We discuss a practical application of this strategy on cyclopentadiene (CPD) to di-cyclopentadiene (DCPD) reactor in an isoprene production unit, The success of the project is shown by the reduction in variability of product losses and in a more stable feed composition to the downstream portion of the production unit. This solution strategy was reached using the rigorous steady-state simulation and a linear controller (Dynamic Matrix Control). Using these tools, it was possible to develop an adaptative controller and to detect the process exothermic behavior, model it and control the controlled variables in a stable manner. This method, using the rigorous model, is especially useful when the process dead time is a large fraction of the process time.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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