(706a) Multivariable Model Predictive Control of a Novel Rapid Pressure Swing Adsorption Process

Abstract for AIChE Conference,
2016                                                                      March
14, 2016

Multivariable Model Predictive
Control of a Novel Rapid Pressure Swing Adsorption Process

Matthew Urich[1], Rama Rao Vemula,
Mayuresh V. Kothare

Department of Chemical and Biomolecular
Engineering, Lehigh University

Bethlehem, PA, USA 18015

            A novel, single bed Rapid Pressure
Swing Adsorption (RPSA) system was developed previously, and details can be
found in [1,2]. The principal objective of this research work is the design of
control algorithm for the operation of a novel, single-bed, 4-step, Rapid
Pressure Swing Adsorption (RPSA) Process. The proprietary RPSA design has an
adsorber enclosed inside a product storage tank which supplies ~90% oxygen
continuously and back purges the column during regeneration steps. A N₂-O₂
gas mixture was selected as the adsorbate and a Li-X zeolite was chosen as an
adsorbent for this modeling and simulation study. A Skarstrom type, 4-step,
RPSA cycle has been implemented for the separation of O₂ from the N₂-O₂
mixture. During the pressurization step, the adsorption column pressurizes to a
super atmospheric pressure from the feed-end with compressed N₂-O₂
mixture. High purity O₂ goes to the storage tank during the adsorption
step from the product-end while compressed N₂-O₂ is continuously
supplied at the feed-end. During the blow down step, the column pressure is
reduced to atmosphere for desorbing the nitrogen from feed-end. During the
purge step, a portion of the high purity oxygen is used to back purge the
column and clean nitrogen from the column voids. A mathematical model of the
RPSA process integrated with the product storage tank was developed from first
principles and the model equations were solved using COMSOL MULTIPHYSICS with
MATLAB. The model incorporates detailed adsorption kinetics, equilibrium
equations, heat effects, mass transfer behavior and pressure effects. To the
best of knowledge, this is the first attempt to incorporate all physical
chemical effects coupled with storage tank dynamics for a dynamic RPSA
simulator. The generation of a control algorithm/scheme is critical for the
optimum operation of RPSA process by controlling the product storage tank pressure,
and oxygen product purity. Most reported control studies only use adsorption
time as a manipulated variable [3,4]. We propose a full multivariable control
architecture which varies all four step times in the cycle as manipulated
variables. The controller uses individual step durations as the manipulated
variables to achieve the control objective. The Model Predictive Controller
presented here uses an identified linear observer model and an optimization
program to optimally achieve the control objectives. Open and closed-loop disturbance
simulations are compared to evaluate the MPC controller performance. The
results obtained from the closed-loop simulations and challenges for
implementing a control structure for RPSA design will be discussed in this presentation.

References:

[1] Chai SW,
Kothare MV, Sircar S. Rapid pressure swing adsorption for reduction of bed size
factor of a medical oxygen concentrator. Ind. Eng Chem Res. 2011; 50: 8703-8710.

[2] Rama Rao V,
Kothare MV, Sircar S. Novel Design and Performance of a Medical Oxygen
Concentrator Using a Rapid Pressure Swing Adsorption Concept. AIChE. 2014; 60: 3330-3335.

[3] Khajuria H,
Pistikopoulos EN. Dynamic modeling and explicit/multi-parametric MPC control of
pressure swing adsorption systems. Journal of Process Control. 2011; 21:
151-163.

[4] Khajuria H,
Pistikopoulos EN. Optimization and control of pressure swing adsorption
processes under uncertainty. AIChE. 2012; 59: 120-131.