Hybrid observer for parameters estimation in ethylene polymerization reactor: A simulation study

Estimating unknown parameters in ethylene polymerization reactor using hybrid Fuzzy-SMO.Display Omitted Novel hybrid observer method combining fuzzy logic with sliding mode observer.The observer is able to estimate several parameters without redesigning the structure of the whole observer.The design is simple and easy to formulate.Provides fast and accurate estimation results in estimating the ethylene, butene and melt index in a polyethylene reactor. In this work, we proposed a novel hybrid fuzzy-sliding mode observer designed in such a manner that it can be utilized to estimate various parameters by simply using the related process model, without redesigning the structure of the whole observer. The performances and effectiveness of this hybrid observer are shown through numerical simulation based on a case study involving an ethylene polymerization process to estimate the ethylene and butene concentrations in the reactor as well as the melt flow index. It can be concluded that the proposed hybrid observer provides fast estimation with a high rate of accuracy even in the presence of disturbances and noise in the model. This hybrid observer is also compared with the sliding mode, extended Luenberger and proportional sliding mode observers to highlight its effectiveness and advantages over these observers.

[1]  Claudio Scali,et al.  Parameter estimation in Extended Kalman Filters for quality control in polymerization reactors , 1996 .

[2]  N Pappa,et al.  Design of a self-tuning regulator for temperature control of a polymerization reactor. , 2012, ISA transactions.

[3]  Thomas J. Harris,et al.  A comparison of two-phase and well-mixed models for fluidized-bed polyethylene reactors , 1994 .

[4]  Philippe Bogaerts,et al.  Hybrid full horizon-asymptotic observer for bioprocesses , 2002 .

[5]  Rafael Martínez-Guerra,et al.  State estimation for nonlinear systems under model unobservable uncertainties: application to continuous reactor , 2005 .

[6]  José Ragot,et al.  Observers design for uncertain Takagi-Sugeno systems with unmeasurable premise variables and unknown , 2011 .

[7]  Petr Husek,et al.  Fuzzy model reference control with adaptation of input fuzzy sets , 2013, Knowl. Based Syst..

[8]  Darci Odloak,et al.  Observer-based fault diagnosis in chemical plants , 2005 .

[9]  A. J. Morris,et al.  Estimation of impurity and fouling in batch polymerisation reactors through the application of neural networks , 1999 .

[10]  V. Chitanov,et al.  Neural-fuzzy modelling of polymer quality in batch polymerization reactors , 2004, 2004 2nd International IEEE Conference on 'Intelligent Systems'. Proceedings (IEEE Cat. No.04EX791).

[11]  Rafael Maya-Yescas,et al.  State Estimation for Nonlinear Systems under Model Uncertainties: A Class of Sliding-Mode Observers , 2005 .

[12]  Ramdhane Dhib,et al.  Unscented Kalman filter based nonlinear model predictive control of a LDPE autoclave reactor , 2011 .

[13]  T. McKenna,et al.  Online Reaction Calorimetry. Applications to the Monitoring of Emulsion Polymerization without Samples or Models of the Heat-Transfer Coefficient , 2002 .

[14]  Sami Othman,et al.  Nonlinear observers for parameter estimation in a solution polymerization process using infrared spectroscopy , 2008 .

[15]  Chengye Zhao,et al.  Melt index prediction based on fuzzy neural networks and PSO algorithm with online correction strategy , 2012 .

[16]  Qunxiong Zhu,et al.  Energy Efficiency Estimation Based on Data Fusion Strategy: Case Study of Ethylene Product Industry , 2012 .

[17]  Marius-Lucian Tomescu,et al.  Fuzzy Logic Control System Stability Analysis Based on Lyapunov's Direct Method , 2009, Int. J. Comput. Commun. Control.

[18]  Hisbullah,et al.  Design of a Fuzzy Logic Controller for Regulating Substrate Feed to Fed-Batch Fermentation , 2003 .

[19]  Oscar Castillo,et al.  A new approach for dynamic fuzzy logic parameter tuning in Ant Colony Optimization and its application in fuzzy control of a mobile robot , 2015, Appl. Soft Comput..

[20]  Philippe Bogaerts,et al.  Parameter identification for state estimation—application to bioprocess software sensors , 2004 .

[21]  M. A. Latifi,et al.  Optimization and non-linear control of a batch emulsion polymerization reactor , 1999 .

[22]  Jie Zhang,et al.  Artificial Intelligence techniques applied as estimator in chemical process systems - A literature survey , 2015, Expert Syst. Appl..

[23]  E. Alpay,et al.  Calorimetric estimation for a batch-loop emulsion polymerisation reactor , 2004 .

[24]  Jialin Liu,et al.  On-line soft sensor for polyethylene process with multiple production grades , 2007 .

[25]  Shuang-Hua Yang,et al.  Neural network based estimation of a semi-batch polymerisation reactor , 1999 .

[26]  Michael J. Kurtz,et al.  On-line state and parameter estimation of EPDM polymerization reactors using a hierarchical extended Kalman filter , 2004 .

[27]  Mohd Azlan Hussain,et al.  Control of a Batch Polymerization System Using Hybrid Neural Network - First Principle Model , 2008 .

[28]  Fumitoshi Matsuno,et al.  Augmented Stable Fuzzy Control for Flexible Robotic Arm Using LMI Approach and Neuro-Fuzzy State Space Modeling , 2008, IEEE Transactions on Industrial Electronics.

[29]  Costas Kravaris,et al.  Advances and selected recent developments in state and parameter estimation , 2013, Comput. Chem. Eng..

[30]  Mohd Azlan Hussain,et al.  Parameter estimations using hybrid observer in an ethylene polymerization process , 2014 .

[31]  Victor M. Zavala,et al.  Optimization-based strategies for the operation of low-density polyethylene tubular reactors: Moving horizon estimation , 2009, Comput. Chem. Eng..

[32]  Claudio Scali,et al.  Control of the quality of polymer products in continuous reactors: comparison of performance of state estimators with and without updating of parameters , 1997 .

[33]  L. Biegler,et al.  A Moving Horizon Estimator for processes with multi-rate measurements: A Nonlinear Programming sensitivity approach , 2012 .

[34]  Francis J. Doyle,et al.  Polymer grade transition control using advanced real-time optimization software , 2004 .

[35]  A. Vande Wouwer,et al.  Improving continuous–discrete interval observers with application to microalgae-based bioprocesses , 2009 .

[36]  V. Utkin,et al.  Sliding mode observers. Tutorial , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[37]  Philippe Bogaerts,et al.  Hybrid extended Luenberger-asymptotic observer for bioprocess state estimation , 2006 .

[38]  E. Ali,et al.  Broadening the polyethylene molecular weight distribution by controlling the hydrogen concentration and catalyst feed rates. , 2010, ISA transactions.

[39]  Hyun-Ku Rhee,et al.  Online estimation and control of polymer quality in a copolymerization reactor , 2002 .

[40]  Joachim Horn,et al.  Trajectory tracking of a batch polymerization reactor based on input–output-linearization of a neural process model , 2001 .

[41]  Masoud Soroush,et al.  Multirate nonlinear state estimation with application to a polymerization reactor , 1999 .

[42]  T. Floquet,et al.  On Sliding Mode Observers for Systems with Unknown Inputs , 2006, International Workshop on Variable Structure Systems, 2006. VSS'06..

[43]  Denis Dochain,et al.  State and parameter estimation in chemical and biochemical processes: a tutorial , 2003 .

[44]  Sarah K. Spurgeon,et al.  Sliding mode observers: a survey , 2008, Int. J. Syst. Sci..

[45]  Mohd Azlan Hussain,et al.  Sliding Mode Control for a Continuous Bioreactor , 2003 .

[46]  Mohd Azlan Hussain,et al.  Hybrid Observer for Chemical Process Systems , 2013 .

[47]  M. Hussain,et al.  CFD simulation of fluidized bed reactors for polyolefin production – A review , 2014 .

[48]  Mohd Azlan Hussain,et al.  Polypropylene Production Optimization in Fluidized Bed Catalytic Reactor (FBCR): Statistical Modeling and Pilot Scale Experimental Validation , 2014, Materials.

[49]  J. Macgregor,et al.  On‐line inference of polymer properties in an industrial polyethylene reactor , 1991 .

[50]  Mohd Azlan Hussain,et al.  Hybrid neural network—prior knowledge model in temperature control of a semi-batch polymerization process , 2004 .

[51]  D. M. Himmelblau,et al.  Online prediction of polymer product quality in an industrial reactor using recurrent neural networks , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

[52]  Sebastian Engell,et al.  Design and implementation of an extended observer for the polymerization of polyethylenterephthalate , 1996 .

[53]  Masahiro Ohshima,et al.  Quality control of polymer production processes , 2000 .

[54]  Jinyoung Kim,et al.  Neural network modeling of temperature behavior in an exothermic polymerization process , 2002, Neurocomputing.

[55]  J. Alvarez,et al.  On the effect of the estimation structure in the functioning of a nonlinear copolymer reactor estimator , 2004 .

[56]  Urban Dominik Mäder,et al.  Augmented Models in Estimation and Control , 2011 .

[57]  T. Crowley,et al.  On-line monitoring and control of a batch polymerization reactor , 1996 .

[58]  M. Rijckaert,et al.  Intelligent modelling in the chemical process industry with neural networks : A case study , 1998 .

[59]  Denis Dochain,et al.  Review and classification of recent observers applied in chemical process systems , 2015, Comput. Chem. Eng..

[60]  J. Macgregor,et al.  A kinetic model for industrial gas-phase ethylene copolymerization , 1990 .

[61]  Masoud Soroush,et al.  Nonlinear State Estimation in a Polymerization Reactor , 1997 .

[62]  Hyun-Ku Rhee,et al.  Extended Kalman filter-based nonlinear model predictive control for a continuous MMA polymerization reactor , 1999 .

[63]  Brian Roffel,et al.  Non-linear model based control of a propylene polymerization reactor , 2007 .