Design of a Hybrid Controller for Pressure Swing Adsorption Processes

The aim of this paper is to synthesize a hybrid controller for pressure swing adsorption (PSA) processes. Since the process is described by a set of partial differential algebraic equations, first a local reduced-order model (LROM) for the process is developed and is formalized as a hybrid system. A hybrid controller is designed for purity control of the process in the presence of external disturbances by determining the maximal safe set of the LROM. A hybrid backward reachability analysis is performed for this purpose. Considering a realistic scenario for PSA processes where the states are not available and the number of measurement sensors is very limited, the desired states are estimated by using a hybrid observer. The controller is designed and applied to a two-bed, six-step PSA process whose dynamical behavior is simulated by a full-order principle-based model of the process. An excellent performance of the controller is obtained.

[1]  Bengt Lennartson,et al.  Hybrid systems in process control , 1996 .

[2]  Claire J. Tomlin,et al.  Guaranteed Safe Online Learning via Reachability: tracking a ground target using a quadrotor , 2012, 2012 IEEE International Conference on Robotics and Automation.

[3]  Ernst Dieter Gilles,et al.  State and parameter estimation for adsorption columns by nonlinear distributed parameter state observers , 1994 .

[4]  Mo Chen,et al.  Using Neural Networks for Fast Reachable Set Computations , 2016, ArXiv.

[5]  Efstratios N. Pistikopoulos,et al.  Dynamic modeling and explicit/multi-parametric MPC control of pressure swing adsorption systems , 2011 .

[6]  Efstratios N. Pistikopoulos,et al.  A dynamic programming based approach for explicit model predictive control of hybrid systems , 2015, Comput. Chem. Eng..

[7]  Lorenz T. Biegler,et al.  Recent Advances in Simulation and Optimal Design of Pressure Swing Adsorption Systems , 2005 .

[8]  Michael Zeitz,et al.  Design of a nonlinear distributed parameter observer for a pressure swing adsorption plant , 2002 .

[9]  Mo Chen,et al.  Fast reachable set approximations via state decoupling disturbances , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[10]  Claire J. Tomlin,et al.  Temporal-difference learning for online reachability analysis , 2015, 2015 European Control Conference (ECC).

[11]  M. Zeitz,et al.  Process Control Scheme for a 2-Bed Pressure Swing Adsorption Plant , 2002 .

[12]  Maria Domenica Di Benedetto,et al.  A hybrid controller for purity control of a pressure swing adsorption process , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[13]  J. Lygeros,et al.  A game theoretic approach to controller design for hybrid systems , 2000, Proceedings of the IEEE.

[14]  Shohreh Fatemi,et al.  A switching decentralized and distributed extended Kalman filter for pressure swing adsorption processes , 2016 .

[15]  Alexandre M. Bayen,et al.  A time-dependent Hamilton-Jacobi formulation of reachable sets for continuous dynamic games , 2005, IEEE Transactions on Automatic Control.

[16]  Tiziano Villa,et al.  Maximal Safe Set Computation for Idle Speed Control of an Automotive Engine , 2000, HSCC.

[17]  Weina Sun,et al.  A Systematic Simulation and Proposed Optimization of the Pressure Swing Adsorption Process for N2/CH4 Separation under External Disturbances , 2015 .

[18]  Fatemi Shohreh,et al.  Comparative simulation study of PSA, VSA, and TSA processes for purification of methane from CO2 via SAPO-34 core-shell adsorbent , 2016 .

[19]  Ian M. Mitchell,et al.  A Toolbox of Level Set Methods , 2005 .

[20]  Wolfgang Marquardt,et al.  Consistent hierarchical economic NMPC for a class of hybrid systems using neighboring-extremal updates , 2014 .

[21]  Juan J. Sanchez.  Use of an Extended Kalman Filter , 1990 .

[22]  Ronald Fedkiw,et al.  Level set methods and dynamic implicit surfaces , 2002, Applied mathematical sciences.

[23]  Shamsuzzaman Farooq,et al.  Comparison of isotherm models for hydrocarbon adsorption on activated carbon , 1996 .

[24]  Enmin Feng,et al.  Identification and robustness analysis of nonlinear hybrid dynamical system concerning glycerol transport mechanism , 2012, Comput. Chem. Eng..

[25]  Efstratios N. Pistikopoulos,et al.  Optimization and Control of Pressure Swing Adsorption Processes Under Uncertainty , 2013 .

[26]  Masaru Noda,et al.  Application of A hybrid control approach to highly nonlinear chemical processes , 2006 .

[27]  Julio R. Banga,et al.  Optimization of hybrid discrete/continuous dynamic systems , 2000 .

[28]  Alberto Bemporad,et al.  Predictive Control for Linear and Hybrid Systems , 2017 .

[29]  B. T. Baumrucker,et al.  MPEC strategies for optimization of a class of hybrid dynamic systems , 2009 .

[30]  Matthias Bitzer,et al.  Model-based nonlinear tracking control of pressure swing adsorption plants , 2005 .

[31]  Alírio E. Rodrigues,et al.  A parametric study of layered bed PSA for hydrogen purification , 2008 .

[32]  Sebastian Engell,et al.  Analyzing safety properties of hybrid processing systems: A case study on an industrial evaporator , 2008 .

[33]  John Lygeros,et al.  Synthesizing Controllers for Nonlinear Hybrid Systems , 1998, HSCC.

[34]  Alexandre M. Bayen,et al.  Aircraft Autolander Safety Analysis Through Optimal Control-Based Reach Set Computation , 2007 .

[35]  Kwang Soon Lee,et al.  Nonlinear observer with adaptive grid allocation for a fixed-bed adsorption process , 2012, Comput. Chem. Eng..