John D. Hedengren, Ph.D.

  Department of Chemical Engineering

  Brigham Young University

 

 

Scientific Interests and Activities

 

Efficient Moving Horizon Estimation of ODE and DAE Systems - Multimedia PowerPoint Tutorial

Haseltine and Rawlings (Ind. Eng. Chem. Res., 2004) definitively showed that Moving Horizon Estimation (MHE) outperforms the Extended Kalman Filter.  Their conclusion was that the only cost of improvement was the greater computational expense of MHE.  The multimedia powerpoint tutorial will demonstrate an explicit solution to MHE (eMHE).  The explicit solution executes up to 10,000x faster than the implicit solution approach.  The explicit solution incorporates all of the recent advances in MHE including a forgetting factor for an infinite horizon approximation, input and output disturbances for offset free estimation and control, and parameter estimation.

 


 

In Situ Adaptive Tabulation (ISAT) for Nonlinear MPC - Multimedia PowerPoint Tutorial   PDF version

ISAT is a computational reduction technique applied to nonlinear model predictive control (NMPC) to make real-time applications feasible.  ISAT was originally developed for turbulent combustion simulations [1] and has recently been added to the popular CFD package, FluentTM   Like artificial neural networks, ISAT is a storage and retrieval method.  Unlike neural nets, ISAT is adaptive to extrapolation.  In addition, ISAT learns as it goes so there is no specified amount of training data before it starts performing.

 

Try out a CSTR simulator with ISAT incorporated NMPC.  A National Instruments plug-in loads automatically.  If someone else is using the simulator you will receive control in 5 minutes.  Click the run button once the program has loaded.  Here is a screen shot of the CSTR simulator. Contact me by e-mail if you would like to use this as a real-time web-application.

 

The first eigenfunction of an L-shaped membrance. The second and third eigenfunctions have also been shown in MathWorks' publications. This animation shows an ISAT approximation to that function. The independent variables are x and y (horizontal axes) and the dependent variable is z (vertical axis). The error tolerance for z is steadily ramped from 0.01 to 0.99. The error tolerance of the current frame is indicated on the figure. Initially at a low error tolerance of 0.01, the approximation is nearly exact but requires 206 ISAT records. When the error tolerance is increased to 0.1, 48 ISAT records are stored. At an error tolerance of 0.5, only 12 ISAT records are required to meet the relaxed error bound. 

 

Unlike artificial neural networks, ISAT has explicit control of the function approximation error and function approximation derivatives. Bounded derivative networks are an attempt to overcome some of the poor extrapolation and interpolation properties of neural networks. ISAT's approach is fundamentally different. Instead of one nonlinear function, ISAT uses multiple linear regions while maintaining explicit error control. 

 

Learn More - ISAT

 


 

Nonlinear Model Library - PowerPoint describing 11 sample models   PDF version

One of the major bottlenecks to successful nonlinear model predictive control (Nonlinear MPC) is the lack of reliable first-principles or hybrid models.  This nonlinear model library is an attempt to create a collaborative environment where chemical process models can be documented and shared.  As collaborators submit models the library will serve as a valuable starting point for the development of more sophisticated models for simulation and control.

 

Learn More - Nonlinear Model Library

 


 

Publications

 

Publication Search

 

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Publications

 

Hedengren, J. D., Advanced Process Monitoring, Chapter submitted to Optimization and Analytics in the Oil and Gas Industry, Volume II: The Downstream, Springer-Verlag, 2012.  [Preprint]

 

Spivey, B. J., Hedengren, J. D. and Edgar, T. F., Constrained Nonlinear Estimation for Industrial Process Fouling, Industrial & Engineering Chemistry Research, DOI: 10.1021/ie9018116, 2010. [Abstract]

 

Hedengren, J. D. and Edgar, T. F., Approximate Nonlinear Model Predictive Control with In Situ Adaptive Tabulation, Computers and Chemical Engineering, Volume 32, pp. 706-714, 2008.  [Preprint],   [Abstract]

 

Hedengren, J. D. and Edgar, T. F., Moving Horizon Estimation - The Explicit Solution, Proceedings of the CPC-VII, Lake Louise, Alberta, Canada, 2006.  [Preprint]

 

Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Real-Time Control, Industrial & Engineering Chemistry Research, Ind. Eng. Chem. Res., Volume 44, Issue 8, pp. 2716 -2724, 2005.  [Paper, Abstract]

 

Hedengren, J. D. and Edgar, T. F., Order Reduction of Large Scale DAE Models, Computers and Chemical Engineering, Volume 29, Issue 10, pp. 2069-2077, 2005.  [Abstract]

 

Journal Publications

 

Spivey, B.J., Hedengren, J.D., and Edgar, T.F., Constrained Control and Optimization of Tubular Solid Oxide Fuel Cells for Extending Cell Lifetime, Submitted to the American Control Conference (ACC), Montréal, Canada, July 2012.   [Preprint]

 

Hedengren, J.D. Allsford, K.V., and Ramlal, J., Moving Horizon Estimation and Control for an Industrial Gas Phase Polymerization Reactor, Proceedings of the American Control Conference (ACC), New York, NY, July 2007.   [Preprint]

 

Hedengren, J.D. and Edgar, T.F., Order Reduction of Large Scale DAE Models, IFAC 16th World Congress, Prague, Czechoslovakia, July, 2005.   [Preprint]

 

Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Real-time Control, Proceedings of the American Control Conference (ACC), Boston, MA, July 2004.  [Paper, Presentation]

Conference Proceedings

Brower, D., Hedengren, J.D., Loegering, C., Brower, A., Witherow, K., and Winters, K., Fiber Optic Monitoring of Subsea Equipment, OMAE2012/84143, Rio de Janiero, Brazil, June 2012.   [Preprint]

 

Jensen, K.R. and Hedengren, J.D., Improved Load Following of a Boiler with Advanced Process Control, submitted to AIChE Spring Meeting, Houston, TX, April 2012.   [Abstract]

 

Hedengren, J.D. and Brower, D., Advanced Process Monitoring of Flow Assurance with Fiber Optics, submitted to AIChE Spring Meeting, Houston, TX, April 2012.   [Abstract]

 

Soderstrom, T.A., Zhang, Y., and Hedengren, J.D., Advanced Process Control in ExxonMobil Chemical Company: Successes and Challenges, CAST Division, AIChE National Meeting, Salt Lake City, UT, Nov 2010.   [Presentation]

 

Spivey, B.J., Hedengren, J.D., and Edgar, T.F., Monitoring of Process Fouling Using First-Principles Modeling and Moving Horizon Estimation, Proc. Applications of Computer Algebra (ACA) Conference, Montréal, Canada, 2009.

 

Spivey, B.J., Hedengren, J.D., and Edgar, T.F., Monitoring of Process Fouling Using First-Principles Modeling and Moving Horizon Estimation, Proc. Texas, Wisconsin, California Control Consortium (TWCCC), Austin, TX, February 2009.   [Presentation]

 

Ramlal, J., Naidoo, V., Allsford, K.V., and Hedengren, J.D., Moving Horizon Estimation for an Industrial Gas Phase Polymerization Reactor, Proc. IFAC Symposium on Nonlinear Control Systems Design (NOLCOS), Pretoria, South Africa, 2007.   [Preprint]

 

Hedengren, J.D. and Edgar, T.F., Order Reduction of a Large-Scale Index-2 DAE Model, Computing and Systems Technology Division, AIChE National Meeting, Cincinnati, OH, Nov 2005.   [Abstract]

 

Hedengren, J. D. and Edgar, T. F., Efficient Moving Horizon Estimation of DAE Systems, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Austin, TX, Feb 2005.   [Presentation]

 

Hedengren, J. D. and Edgar, T. F., Adaptive DAE Model Reduction, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Madison, WI, Sept 2004.   [Presentation]

 

Hedengren, J. D. and Edgar, T. F., Order Reduction of Large Scale DAE Models, Computing and Systems Technology Division, AIChE National Meeting, Austin, TX, Nov 2004.   [Paper, Presentation]

 

Hedengren, J. D. and Edgar, T. F., Dependency Analysis for DAE to ODE Conversion and Model Reduction, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Austin, TX, Feb 2004.   [Paper]

 

Hedengren, J. D., In Situ Adaptive Tabulation for Real-time Control, Admission to Candidacy, 9 Dec. 2003 - Himmelblau Library (CPE 4.446).  [Paper, Presentation]

 

Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Nonlinear MPC, Poster Session: Systems and Process Control, AIChE National Meeting, San Francisco, CA, Nov 2003.   [Paper]

 

Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Nonlinear MPC, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Madison, WI, Sept 2003.   [Presentation]

 

Other Publications

 

Hedengren, J. D., A Nonlinear Model Library for Dynamics and Control, Computer Aids for Chemical Engineering (CACHE) News, Summer 2008.  PDF

 

Contributed to:

Beucher, O. and M. Weeks, Introduction to MATLAB & SIMULINK: A Project Approach, 3rd Edition, Infinity Science Press, 2008.  Amazon Book Search

 

Masters Thesis

 

Hedengren, J. D., Implementation of Automatically Simplified Chemical Kinetics through Intrinsic Low-Dimensional Manifolds for Gaseous HMX, Masters Thesis, Brigham Young University, 2002.  Abstract (10 KB)  Full (852 KB)

 

Doctoral Dissertation

 

Hedengren, J. D., Real-Time Estimation and Control of Large-Scale Nonlinear DAE Systems, Doctoral Dissertation, The University of Texas at Austin, 2005.  PDF (1.4 MB)

 

Education

 

The University of Texas at Austin, Austin, TX

Doctor of Philosophy in Chemical Engineering, May 2005  GPA: 4.0

 

Brigham Young University, Provo, Utah

Bachelor of Science in Chemical Engineering, May 2001  GPA: 3.96

Master of Science in Chemical Engineering, Aug. 2002  GPA: 3.9

 

Experience

Assistant Professor, Brigham Young University, Provo, UT (Aug 2011-Current)

Develop efficient modeling and optimization methods for large-scale dynamic systems

Analyze measurements of complex systems to gain fundamental process insight

Design, monitor, and optimize energy systems

 


ExxonMobil Chemical Applications Engineer, Baytown, Texas (April 2007-August 2011)
Developed advanced process control for polymer production
Worked with plant operators and technical specialists to commission nonlinear control (NLC) applications

 


APMonitor Software Developer, Web-site, Houston, Texas (Feb 2007-March 2007)
Developed innovative modeling, simulation, and control software
Applied software to monitor developmental and industrial applications

        

Advanced Process Control and Optimization Software Development, PAS, Inc., Clearlake, TX (May 2005-Jan 2007)

Developed first principles models for homopolymer and impact co-polymer polypropylene reactors
Commissioned 3 Unipol polypropylene nonlinear model predictive controllers (NMPC)

Conducted APC training seminars for internal and external clients
Worked on a team to commission a HIPS (High-Impact Polystyrene) APC application

 

Advanced Process Control Research, University of Texas at Austin, Austin, TX (Sept. 2002-May 2005)
Developed methods to significantly reduce nonlinear model predictive control (MPC) computational time
Explored large-scale model reduction for differential algebraic models (DAEs)
Currently developing real-time advanced control strategies for industrial use

 


ExxonMobil Process Control Internship, Baytown, Texas (April 2004-June 2004)
Developed advanced process control (APC) for polymer production
Worked with plant operators and technical specialists to develop a model
Trained fellow engineers to use advanced control technology

Rocket Propellant Combustion Modeling, Brigham Young University, Provo, UT (May 2001-Aug. 2002)

Worked on University of Utah’s ASCI C-SAFE program (www.csafe.utah.edu)

Explored ‘time to detonation’ of a rocket motor in a pool fire

Developed an algorithm to reduce computational time of a chemistry calculation by ten times

CH2MHill Internship, Hanford, Washington (June 2000-Aug. 2000)

Determined pipe flushing requirements for radioactive waste

Worked on a team to maintain liquid pumping from radioactive waste tanks

 

BNFL Inc. Internship, Hanford, Washington (June 1999-Aug. 1999)

Performed design work for a vitrification facility through extensive corrosion analysis

Prepared reports for the US Department of Ecology and other clients

 

BYU DIPPR Thermophysical Properties Lab, Brigham Young University, Provo, UT (April 1999-June 1999)

Predicted surface tensions for over 700 compounds using Parachor values

 

Contact Information

 

Department of Chemical Engineering 
Brigham Young University 
Provo, UT 84602 
USA