Robust characteristic-based MPC of a fixed-bed reactor

Abstract

In this work a model predictive control methodology is applied to a set of hyperbolic partial differential equations (PDEs) which models a chemical fixed-bed reactor. Initially, the model of the fixed-bed reactor is linearized and by the method of characteristics is transformed into the set of ODEs which is explored within the model predictive controller synthesis. We consider uncertainties present in the reactor model which are taken into account by the construction of the polytopic family of plants and subsequent robust model predictive controller synthesis which ensures input and state constraints satisfaction. The proposed robust control problem formulation and the performance of the controller have been evaluated by simulations.

Model Predictive Control for First-Order Hyperbolic System Based on Quasi-Shannon Wavelet Basis

“…It has been applied to the study of control problems, where the SO 2 concentration is to be controlled in a circulating fluidized bed [27]. It has also been applied to uncertain hyperbolic systems [28], and a counterflow plug-flow reactor [29]. On the other hand, model predictive control based on the weighted residual method is being developed for hyperbolic systems.…”

Model order reduction of hyperbolic systems using method of characteristics and differential transform

“…Recently, Sudhakar et al (2013a,b) have proposed to use method of characteristic (MOC) for hyperbolic PDEs to obtain lower order model and such lower order model reasonably approximates the higher order solution. Although there are works related to the use of MOC for hyperbolic PDEs (Knuppel et al, 2010;Mohammadi et al, 2010;Fuxman et al, 2007;Shang et al, 2004;Choi, 2007;Choi and Lee, 2005), the approximation proposed by Sudhakar et al (2013a,b) results in model of significantly lower order. In the application of MOC, initial and boundary value problems are solved repeatedly over smaller intervals.…”