Advanced step nonlinear model predictive control for air separation units

Cryogenic air separation units constitute an integral part of many industrial processes and next generation power plants. These units are characterized by fluctuating operating conditions to respond to changing product demands. The dynamics of these transitions are highly nonlinear and energy-intensive. Consequently, nonlinear model predictive control (NMPC) based on rigorous dynamic models is essential for high performance in these applications. Currently, the implementation of NMPC controllers is limited by the computational complexity of the associated on-line optimization problems. In this work, we make use of the so-called advanced step NMPC controller to overcome these limitations. We demonstrate that this sensitivity-based strategy reduces the on-line computational time to just a single CPU second, while incorporating a highly detailed dynamic air separation unit model. Finally, we demonstrate that the controller can handle nonlinear dynamics over a wide range of operating conditions.

[1]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[2]  Lorenz T. Biegler,et al.  An MPEC formulation for dynamic optimization of distillation operations , 2004, Comput. Chem. Eng..

[3]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[4]  Brian Roffel,et al.  First principles dynamic modeling and multivariable control of a cryogenic distillation process , 2000 .

[5]  Johannes P. Schlöder,et al.  Real-Time Optimization for Large Scale Processes: Nonlinear Model Predictive Control of a High Purity Distillation Column , 2001 .

[6]  Lorenz T. Biegler,et al.  Dynamic Process Optimization through Adjoint Formulations and Constraint Aggregation , 1999 .

[7]  Rüdiger Franke,et al.  Integration of Advanced Model Based Control with Industrial IT , 2007 .

[8]  Frank Allgöwer,et al.  Assessment and Future Directions of Nonlinear Model Predictive Control , 2007 .

[9]  R. Sargent,et al.  Solution of a Class of Multistage Dynamic Optimization Problems. 2. Problems with Path Constraints , 1994 .

[10]  L. Biegler,et al.  Advances in simultaneous strategies for dynamic process optimization , 2002 .

[11]  David R. Vinson,et al.  Air separation control technology , 2006, Comput. Chem. Eng..

[12]  L. Biegler,et al.  A fast moving horizon estimation algorithm based on nonlinear programming sensitivity , 2008 .

[13]  Zoltan K. Nagy,et al.  Real-Time Implementation of Nonlinear Model Predictive Control of Batch Processes in an Industrial Framework , 2007 .

[14]  R. Reid,et al.  The Properties of Gases and Liquids , 1977 .

[15]  Lawrence Megan,et al.  Compartmental modeling of high purity air separation columns , 2005, Comput. Chem. Eng..

[16]  M. Diehl,et al.  Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations , 2000 .

[17]  Lorenz T. Biegler,et al.  On-line implementation of nonlinear MPC: an experimental case study , 2000 .

[18]  E. Camacho,et al.  Nonlinear Model Predictive Control: An Introductory Review , 2007 .

[19]  Sebastian Engell,et al.  Non-linear model predictive control of the hashimoto simulated moving bed process , 2007 .

[20]  Oskar von Stryk,et al.  Towards Nonlinear Model-Based Predictive Optimal Control of Large-Scale Process Models with Application to Air Separation Plants , 2001 .

[21]  Frank Allgöwer,et al.  Computational Delay in Nonlinear Model Predictive Control , 2004 .

[22]  Lorenz T. Biegler,et al.  Convergence rates for direct transcription of optimal control problems using collocation at Radau points , 2008, Comput. Optim. Appl..

[23]  R. Donald Bartusiak,et al.  NLMPC: A Platform for Optimal Control of Feed- or Product-Flexible Manufacturing , 2007 .

[24]  Efstratios N. Pistikopoulos,et al.  PARAMETRIC MODEL PREDICTIVE CONTROL OF AIR SEPARATION , 2006 .

[25]  Victor M. Zavala,et al.  The advanced-step NMPC controller: Optimality, stability and robustness , 2009, Autom..

[26]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1972 .

[27]  Peter Deuflhard,et al.  Numerical Treatment of Inverse Problems in Differential and Integral Equations: Proceedings of an International Workshop, Heidelberg, Fed. Rep. of Germany, August 30 - September 3, 1982 , 2012 .

[28]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..