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Rullo P.,Computer Aided for Process Engineering Group CAPEG | Nieto Degliuomini L.,Computer Aided for Process Engineering Group CAPEG | Garcia M.,Computer Aided for Process Engineering Group CAPEG | Basualdo M.,Computer Aided for Process Engineering Group CAPEG | Basualdo M.,National University of Costa Rica
International Journal of Hydrogen Energy | Year: 2014

In this work, a conventional plant wide control of a hydrogen production process from bioethanol is analyzed. The objective is to determine if the carbon monoxide (CO), in the produced hydrogen, exceeds the Proton Exchange Membrane Fuel Cell quality requirement of 10 ppm. Commercial sensors that meet those process conditions at high temperature are not easily available. Then, the development of two soft sensors, based on neural network, for online estimation of CO concentration in the H2 stream is presented. Higher CO concentration than allowed is detected in the fuel cell feeding. Strong interaction effects among the control loops around the last reactor, are found. Based on this, two model predictive control technologies are tested and compared in this interacted zone, in order to improve the disturbance rejection and satisfy the H2 expected quality. An exigent disturbance profile was used for simulating dynamically the complete process behavior. © 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.


Nieto Degliuomini L.,Computer Aided for Process Engineering Group CAPEG | Nieto Degliuomini L.,National University of Costa Rica | Zumoffen D.,Computer Aided for Process Engineering Group CAPEG | Zumoffen D.,National University of Costa Rica | And 2 more authors.
International Journal of Hydrogen Energy | Year: 2012

The main contribution of this work is the application of a novel technique for the plant-wide control design to a challenging bio-ethanol processor system for hydrogen production. It is based on steam reforming, followed by high and low-temperature shift reactors and preferential oxidation. The obtained hydrogen feeds a fuel cell for automotive use. The control structure is defined by using a well-tested, systematic and generalized procedure, named minimum square deviation. It allows keeping the process at the operating point of maximum efficiency. This design procedure accounts both, set point as well as disturbances effects which can be sorted according to their importance through specific weighting matrices. The first step of this approach solves the problem of obtaining the best-controlled variables. Then, the search involves testing several combinations between the available input-output variables. The overall processor system with fuel cell, able for doing the tests, was modeled by using mass and energy balances, chemical equilibrium, thermodynamic models and feasible heat transfer conditions. The selected control structure is rigorously tested applied in the dynamic model of the complete plant. The computational implementation of this model was made by using a suitable integration of three well-known programs: MATLAB, HYSYS and ADVISOR. The simulations are performed for hybrid vehicle (PEMFC and supercapacitors). The disturbance profile corresponds to a urban standard driving cycle, which is one of the most exigent. The conclusions are based on fuel consumptions, typical performance indexes used for control strategy evaluations and a trade-off between cost investments and efficiency. © 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.


Nieto Degliuomini L.,Computer Aided for Process Engineering Group CAPEG | Nieto Degliuomini L.,CONICET | Biset S.,Computer Aided for Process Engineering Group CAPEG | Biset S.,National Technological University of Rosario | And 5 more authors.
International Journal of Hydrogen Energy | Year: 2012

A pseudo dynamic rigorous model of a bio-ethanol processor system (BPS) to produce hydrogen for feeding a Proton Exchange Membrane Fuel Cell (PEM-FC) is presented. The main contribution of this work is to give the overall set of differential and algebraic equations (DAE), assumptions and the way to computationally implement it. This model is able for testing the dynamic behavior of this integrated process, obtaining a reduced order linear model and checking any plant-wide control structure design. It is implemented in two programs, HYSYS and MATLAB, properly communicated to coordinate the calculations performed on each one. A part of the process considered with a faster dynamic than the rest of the units of the plant are simulated in HYSYS environment working in steady state mode. Then, auxiliary equipments and the heat exchangers network are in HYSYS which is called by MATLAB every integration interval for doing the simulation of the complete system. On the other side, the PEM-FC and the dynamic models of the plug flow reactors are developed in MATLAB workspace. Hence, strictly speaking this model must be considered as "pseudo" dynamic. The linearized and reduced order model is developed by applying system identification techniques on the rigorous model. Therefore, accounting the main objectives of the process and the most critical disturbances, a preliminary control structure can be well-tested here. Several results are presented in this work analyzing the obtained performances for opened and closed loop modes. © 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.


Zumoffen D.,Computer Aided for Process Engineering Group CAPEG | Molina G.,Computer Aided for Process Engineering Group CAPEG | Nieto L.,Computer Aided for Process Engineering Group CAPEG | Basualdo M.,Computer Aided for Process Engineering Group CAPEG
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2011

This work focuses on the challenging process called Petlyuk distillation column. This plant has interesting properties for reducing the energy consumption up to 30% and the capital investment cost. However the dynamic control of the divided-wall column has been explored in a relatively small number of papers. The control problem is more difficult here since the six sections of the column are coupled. In this work, the control problem is addressed systematically by determining the optimal number of controlled variables (optimal sensor location, OSL) and the control structure design (CSD), simultaneously. It is done by grouping both problems in a single procedure called minimum squared deviation (MSD). This strategy considers both set points and disturbances effect, and the interaction in the controller structure (diagonal, full or sparse) is taking into account, via net load effect (NLE) index, for deciding the best one. A comparison of the dynamic controllability with two other strategies such as self-optimizing control and null space method is presented here. © 2011 IFAC.

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