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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
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.
Nonlinear Model Database - 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 database is an attempt to create a collaborative environment where chemical process models can be documented and shared. As collaborators submit models the database will serve as a valuable starting point for the development of more sophisticated models for simulation and control.
Learn More - Nonlinear Model Database
Publications
Peer Reviewed
Hedengren, J. D. and Edgar, T. F.,
Approximate Nonlinear Model Predictive Control with In Situ Adaptive Tabulation,
Computers and Chemical Engineering, Volume 32,
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,
Hedengren, J. D. and Edgar, T. F.,
Order Reduction of Large Scale DAE Models, Computers and Chemical
Engineering, Volume 29, Issue 10, Conference Publications 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. 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 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., Order Reduction of Large Scale DAE Models, IFAC 16th World Congress, Prague, Czechoslovakia, July, 2005. [Preprint]
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., In Situ Adaptive Tabulation for Real-time Control, Proceedings of the American Control Conference (ACC), Boston, MA, July 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
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
Advanced Process Control and Optimization Software Development, PAS, Inc., Clearlake, TX (May 2005-Current)
Developed first principles models for homopolymer and impact co-polymer
polypropylene reactors
Conducted APC training seminars for internal and external clients
Advanced Process Control Research, University of Texas at Austin, Austin,
TX (Sept. 2002-May 2005)
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
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