Control structure design for the ammonia synthesis process

Abstract

a b s t r a c tThis paper discusses the application of the plantwide control design procedure of Skogestad [Skogestad, S. (2004a). Control structure design for complete chemical plants. Computers and Chemical Engineering, 28,[219][220][221][222][223][224][225][226][227][228][229][230][231][232][233][234] to the ammonia synthesis process. Three modes of operation are considered: (I) given feed rate, (IIa) maximum throughput, and (IIb) "optimized" throughput. Two control structures, one for Mode I and another for Mode IIb, are proposed. In Mode I, it is proposed to keep constant purge rate and compressor powers. There is no bottleneck in the process, and thus there is no Mode IIa of operation. In Mode IIb, the compressors are at their maximum capacity and it is proposed to adjust the feed rate such that the inert concentration is constant. The final control structures result in good dynamic performance.

Development and application of an automatic tool for the selection of control variables based on the self-optimizing control methodology

“…The initiative was inspired by previous work (Araujo and Skogestad, 2007a;Araujo and Skogestad, 2007b;Baldea, Araujo, and Skogestad, 2008;Araujo and Skogestad, 2008;Araujo and Shang, 2009a;Araujo and Shang, 2009b;Araujo and Shang, 2009c) applying the self-optimizing control to chemical process systems, confirming the efficiency of the method. However, these studies used independent and unrelated pieces of software such as Matlab ® , AspenPlus ® and Microsoft Excel ® in a decentralized fashion via extremely tedious computations and data manipulation, which of course is only permissible in an academic environment, never to be used by practitioner process engineers A friendly interface for problem configuration, storage of data, and display of results, along with very efficient routines to compute the gain matrix (first order information), second order information (Hessian of cost function), rank of matrices, and subsets of variables that maximize the minimum singular value of submatrices (bidirectional branch-and-bound), make this proposition unique and, to the authors' knowledge, never attempted before in the plantwide control community.…”

“…Many authors have reported results of the use of the selfoptimizing control technology that ensure the efficiency of the method applied to a great variety of test-bed examples (e.g., Jensen and Skogestad, 2007a;Jensen and Skogestad, 2007b;Hori and Skogestad, 2007a,b;Lersbamrungsuk et al, 2008;Jagtap et al, 2011;Panahi and Skogestad, 2012;Gera et al, 2013;Jaschke and Skogestad, 2014;Khanam et al, 2014;Graciano et al, 2015). Moreover, application of this technology to different case studies using process simulators has also been reported in the literature (Araujo and Skogestad, 2007a;Araujo and Skogestad, 2007b;Baldea, Araujo, and Skogestad, 2008;Araujo and Skogestad, 2008;Araujo and Shang, 2009a;Araujo and Shang, 2009b;Araujo and Shang, 2009c), and the results showed the feasibility and ease of implementation of the self-optimizing control procedure in such instances. However, much effort and time is usually expended doing many mathematical computations using different pieces of software quite alike from one another.…”

“…Studies like the ones reported by Araujo and Skogestad (2007a), Araujo and Skogestad (2007b), Araujo and Skogestad (2008), and in the PhD thesis of Araujo (2007) under the supervision of Dr. Sigurd Skogestad, use mathematical models of whole large scale processes at steady state derived from the commercial simulator Aspen Plus®. From these models, simulations are performed and the information needed to obtain the gain matrix G' is read in Microsoft Excel® with the aid of the OLE technology (Windows® Object Linking and Embedding).…”

Model predictive control for the self-optimized operation in wastewater treatment plants: Analysis of dynamic issues

“…Umar et al, 2012) the dynamic validation of results is usually performed by means of decentralized PI controllers, making a previous pairing with variables (Larsson et al, 2001;Araujo and Skogestad, 2008). In Alstad (2005), the dynamic performance has been improved adding compensators on the measurements to avoid right half plane zeros, and the effect of the basis vectors for the null space method on poles and zeros has been studied.…”

“…When there are active constraints only for manipulated variables, it is straightforward to keep constant the corresponding variable. For example, in Araujo and Skogestad (2008) the operation is optimal for maximum cooling in the heat exchangers for the ammonia synthesis process. In other situations, when constraints are active for some measurements, decoupled PI controllers based on the RGA matrix study are proposed (Alstad, 2005;Gera et al, 2013).…”