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1 Click to edit Master title stle APMonitor Modeling Langage John Hedengren Brigham Yong Universit Advanced Process Soltions LLC
2 Overview of APM Software as a service accessible throgh: MATLAB Pthon Web-browser interface Lin / Windows / Mac OS / Android platforms Solvers APOPT 1 BPOPT 1 IPOPT 2 SNOPT 3 MINOS 3 Problem characteristics: Large-scale Nonlinear Programming NLP Mied Integer NLP MINLP Mlti-objective Real-time sstems Differential Algebraic Eqations DAEs min J z s t f z t g z h z n m z 1 APS LLC 2 EPL 3 SBS Inc m Oct Advanced Process Soltions LLC
3 Overview of APM Vector / matri algebra with set notation Atomatic Differentiation Eact 1 st and 2 nd Derivatives Large-scale sparse sstems of eqations Object-oriented access Thermo-phsical properties Database of preprogrammed models Parallel processing Optimization with ncertain parameters Cstom solver or model connections Oct Advanced Process Soltions LLC
4 Advanced Process Soltions LLC Oct Uniqe Featres of APM Initialization with nonlinear presolve Eplicit variable sbstittion ever fnction call min h g t f s t J min h t f g g s t J Intermediate Variables min h g t f s t J min h g t f st J min h g t f st J min h g t f st J min h g t f st J
5 Uniqe Featres of APM Model development workflow Stead State Dnamic Seqential Simlate Estimate Optimize Solve higher inde DAEs Inde 3+ with APM Inde-1 onl eg MATLAB ode15s Inde-1 + Inde-2 Hessenberg eg DASPK Classes of problems LP QP NLP DAE MILP MIQP MINLP MIDAE Oct Advanced Process Soltions LLC
6 Solver Benchmarking Hock-Schittkowski Percentage % APOPT+BPOPT APOPT 1 BPOPT 1 IPOPT 31 IPOPT 23 SNOPT 61 MINOS Not worse than 2 times slower than the best solver Oct Advanced Process Soltions LLC
7 Solver Benchmarking - Dnamic Optimization Percentage % APOPT+BPOPT APOPT 1 BPOPT 1 IPOPT 31 IPOPT 23 SNOPT 61 MINOS Not worse than 2 times slower than the best solver Oct Advanced Process Soltions LLC
8 Solver Benchmarking SBML Percentage % APOPT+BPOPT APOPT 1 BPOPT 1 IPOPT 31 IPOPT 23 SNOPT 61 MINOS Not worse than 2 times slower than the best solver Oct Advanced Process Soltions LLC
9 Comptational Biolog Drg treatment and discover large-scale models HIV Virs Simlation LogVirs Logkr time ears Oct Advanced Process Soltions LLC
10 Biological Click Kinetic to edit Models Master Modestl title stlesized # of Models Mean = 2 Median = 1 2 # of Phsical Entities Model sizes from 49 crated models in the Biomodels repositor
11 Model Click Size to Limited edit Master b Tools title stle We need better tools parameter estimation optimization to deal with large models! Large ErbB signalling model ~54 phsical entities* Parameter estimation simlated annealing took 24 hors on a 1-node clster compter *Chen et al Mol Sst Biol 29;5:239
12 Smart Grid Energ Sstems Oct Advanced Process Soltions LLC
13 Solid Oide Fel Cells Fel Power to Grid Oct Advanced Process Soltions LLC
14 Flow Assrance for Oil and Gas Indstr Foling and Plgging largest loss categor Billions $$$ per ear in lost revene Predictive Analtics Real-time or Off-line Monitoring Soltion Empirical and First Principles Models Safe Operations Reliabilit Targets Reglator Reports Maimize Economics Training Simlators Oct Advanced Process Soltions LLC
15 Engineering in Remote Locations Oct Advanced Process Soltions LLC
16 Environmental Impact Safe environmentall friendl and economic operations Safet: Velocit of Inlet Waste Gas Safet: LEL of Waste Gas Economic: Fel Costs Environmental: Emission Levels Economic: Size / Inslation Oct Advanced Process Soltions LLC
17 Unmanned Aerial Sstems Oct Advanced Process Soltions LLC
18 UAS Sstem Dnamics Cable-droge dnamics sing Newton 2 nd law Oct Advanced Process Soltions LLC
19 Dnamic Sstem Eample Model Parameters! time constant ta = 5! gain K = 2! maniplated variable = 1 End Parameters Variables! otpt or controlled variable = 1 End Variables Eqations! first order differential eqation ta * $ = - + K * End Eqations End Model Oct Advanced Process Soltions LLC
20 Optimization Under Uncertaint Maniplated Conservative movement based on worst case CV opt Controlled 1 5 Upper Limit opt Oct Advanced Process Soltions LLC
21 Selecting a Model for Predictive Control Man model forms Linear vs Non-linear Stead state vs Dnamic Empirical vs First Principles Select the simplest model Accrac reqirements Stead State Gain Dnamics Time to Stead State Speed reqirements PID < Linear MPC < Nonlinear MPC Continos Form SS A B C D Discrete Form SS [ k [ k] C Nonlinear Model f 1] A p d g p d h p d d d d [ k] B [ k] D [ k] d c d [ k] Oct Advanced Process Soltions LLC
22 Friction Stir Welding A rotating tool creates heat and plasticizes the metal This allows the metal to be stirred together Oct Advanced Process Soltions LLC
23 Getting Started with APM Download Software at Bi-weekl Webinars Oct Advanced Process Soltions LLC
24 Applications Deploed for Real-time Sstems Oct Advanced Process Soltions LLC
25 Ftre Development Plans APM Modeling Langage MI-DAE sstems Active Development Efforts Mied Integer solvers that eploit DAE strctre Interfaces to other scripting langages Indstrial and Academic Collaborators APOPT and BPOPT MINLP solver development Additional information at INFORMS session WC4 Oct Advanced Process Soltions LLC
Click to edit Master title style
Click to edit Master title style APOPT and BPOPT: New NLP and MINLP Solvers for Differential Algebraic Systems with Benchmark Testing John D. Hedengren Jose L. Mojica Brigham Young University Kody M. Powell
Click to edit Master title style
Click to edit Master title style Fast Model Predictive Control Trevor Slade Reza Asgharzadeh John Hedengren Brigham Young University 3 Apr 2012 Discussion Overview Models for Fast Model Predictive Control
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