Analysis of Advanced Process Control Technology and Economic Assessment Improvement

Advanced Process Control (APC) is considered for investment after the Distributed Control System (DCS) and Historian System of Industrial Automation and Control Systems (IACS) had been implemented. The benefits of APC application can be observed by economic assessment (EA), however the EA technique is still behind the development of APC technology. We review the literature on APC and EA and highlight the potential future development

Multivariable Nonlinear Model Predictive Control for a Petroleum Refinery: Multivariable Nonlinear Model Predictive Control for a Petroleum Refinery

This paper presents a detailed procedure to develop a mathematical modelling and simulation of a distillation column for a real feedstock from a condensate processing plant as an initial step of a project feasibility study. The mathematical model of overall dynamics is established on the dynamic continuity equations of the mass and the energy for each unit operation where the mass and the energy can accumulate. The paper provides a case study tutorial for a typical petroleum refinery engineering design. The dynamic analysis and controller for the distillation systems are extremely complicated due to their nonlinearity and multivariable. A nonlinear model predictive control (NMPC) computational scheme for with soften constraints is developed to verify the applicable ability of a direct NMPC controller for a distillation column dealing with the disturbance and the model-plant mismatch as the influence of the plant feed disturbances

On generalized terminal state constraints for model predictive control

This manuscript contains technical results related to a particular approach for the design of Model Predictive Control (MPC) laws. The approach, named "generalized" terminal state constraint, induces the recursive feasibility of the underlying optimization problem and recursive satisfaction of state and input constraints, and it can be used for both tracking MPC (i.e. when the objective is to track a given steady state) and economic MPC (i.e. when the objective is to minimize a cost function which does not necessarily attains its minimum at a steady state). It is shown that the proposed technique provides, in general, a larger feasibility set with respect to existing approaches, given the same computational complexity. Moreover, a new receding horizon strategy is introduced, exploiting the generalized terminal state constraint. Under mild assumptions, the new strategy is guaranteed to converge in finite time, with arbitrarily good accuracy, to an MPC law with an optimally-chosen terminal state constraint, while still enjoying a larger feasibility set. The features of the new technique are illustrated by three examples.Comment: Part of the material in this manuscript is contained in a paper accepted for publication on Automatica and it is subject to Elsevier copyright. The copy of record is available on http://www.sciencedirect.com

Modeling and Control of Distillation Column in a Petroleum Process

This paper introduces a calculation procedure for modeling and control simulation of a condensate distillation column based on the energy balance (-) structure. In this control, the reflux rate and the boilup rate are used as the inputs to control the outputs of the purity of the distillate overhead and the impurity of the bottom products. The modeling simulation is important for process dynamic analysis and the plant initial design. In this paper, the modeling and simulation are accomplished over three phases: the basic nonlinear model of the plant, the full-order linearised model, and the reduced-order linear model. The reduced-order linear model is then used as the reference model for a model-reference adaptive control (MRAC) system to verify the applicable ability of a conventional adaptive controller for a distillation column dealing with the disturbance and the model-plant mismatch as the influence of the plant feed disturbances

Model Predictive Control of Gas Processing Plant Focused on Depropanizer Column

The objective of this project is to improve the energy efficiency and reduce the operation cost for gas processing plant focused on de-propanizer column by implemented the advance process control namely Model Predictive Control. In gas processing plant, 60% of energy used for chemical industries is from distillation processes. To improve the energy efficiency ofdistillation column for gas processing plant, model predictive control is one of technology introduced to the distillation process control system that will overcome this problem compare to conventional controller. In this project, a study 2x2 model predictive control which consist of two manipulate variable and two control variable for de-propanizer column of gas processing plant. By doing the model predictive controller implementation, plant model development which consists of steady state and dynamic model is required by using HYSYS simulation. Step test is necessary which will then calculate the transfer function by using MATLAB system identification for model predictive control design and implementation. And lastly, Comparison between model predictive control and a conventional controller is desired which shown that model predictive controller has better performance and small energy consumption compare to conventional controller

Optimasi Ekonomi Dan Komposisi Produk Pada Debutanizer Menggunakan Economic Model Predictive Control (EMPC)

Debutanizer merupakan kolom distilasi yang digunakan pada unit fraksinasi LPG untuk mendapatkan butane dan senyawa naptha. Kolom distilasi mengkonsumsi sejumlah energi yang besar yang digunakan sebagai pendinginan dan pemanasan pada kolom distilasi. Kebutuhan energi sebesar itu menyebabkan biaya produksi yang digunakan pada kolom distilasibesar.Economic Model Predictive Control (EMPC) diperlukan untuk mengintegrasikan pengendalian proses dan optimasi biaya pada proses atau ekonomi. EMPC adalah penggabungan fungsi objektif MPC secara umum yaitu meminimimalkan error komposisi dan energi dengan mempertimbangkan harga material yang digunakan pada kolom distilasi. Harga material yang digunakan meliputi harga umpan, harga energi, dan harga produk. EMPC berhasil mengoptimasi komposisi sesuai dengan nilai yang ditentukan yaitu 0,4639 untuk komposisi XD dan 0,001 untuk komposisi XB. Saat laju aliran umpan naik, energi yang digunakan sebesar 3.506.729,12 kj/h dan mampu menghemat biaya operasional sebesar 0,37 USD/h sedangkan saat laju aliran umpan turun energi yang digunakan sebesar 2.904.299,34 kj/h dan mampu menghemat biaya operasional sebesar 0,78 USD/h. ================================================================================================================== Debutanizer is a distillation column used on LPG fractionation unit to get butane and naphtha compound. Butane will be sold as LPG, while naphtha is used to add the octane rating in gasoline. The distillation column consumes large amounts of energy. 50% of the energy needs of the industry is used for cooling and heating in the distillation column. Amounts of energy needs that much causes the production costs used on a distillation column become high.Economic Model Predictive Control (EMPC) needs to integrate the control of process and optimization the costs of process or economic. EMPC is merging MPC objective function in general that minimize composition and energy error with consideration of the price of the material used in the distillation column. Prices of materials used include the price of feed, energy prices, and prices of products. EMPC managed to optimize the composition according to the specified values that are 0,4639 for the XD composition and 0,001 for the XB composition. When the flow rate is feed up, the energy used is 3,506,729.12 kj / h and able to save on operating costs of 0,37 USD/h whereas when the flow rate is feed down, the energy used is 2,904,299.34 kj / h and able to save on operating costs of 0,78 USD/h