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Dynamic Optimization
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ControlTypes.ipynb
ControllerObjective.ipynb
ControllerTuning.ipynb
DeepLearning.ipynb
DiscreteVariables.ipynb
DynamicControl.ipynb
DynamicData.ipynb
DynamicModeling.ipynb
DynamicOptimization.ipynb
DynamicOptimizationBenchmarks.ipynb
EstimationObjective.ipynb
EstimatorTuning.ipynb
EstimatorTypes.ipynb
ModelFormulation.ipynb
ModelInitialization.ipynb
ModelSimulation.ipynb
ModelingLanguages.ipynb
MovingHorizonEstimation.ipynb
MultiObjectiveOptimization.ipynb
NonlinearControl.ipynb
OrthogonalCollocation.ipynb
README.md
TCLabA.ipynb
TCLabB.ipynb
TCLabC.ipynb
TCLabD.ipynb
TCLabE.ipynb
TCLabF.ipynb
TCLabG.ipynb
TCLabH.ipynb

README.md

APMonitor-do

Dynamic Optimization

Following is a colab (jupyter notebook) version of the Dynamic Optimization course taught by Dr. John Hedengren at the Brigham Young University. Best method to view these notebooks is in google colab.

Original course website: http://apmonitor.com/do/index.php/Main/HomePage

The goal of this effort is to help students on the following:

  • Follow lectures and solve code in the same location
  • Python packages are upgraded automatically in the colab
  • GEKKO pip installation is verified at each code run
  • Try new code techniques to solve problem
  • Run code in the browser

Currently, GEKKO and ODEINT code are functional in these notebooks. APM code, MATLAB code, lab assignments and exams are a work in progress (link is provided to original website in latter case).

Start Here

Colab version of course: https://github.com/misbahsy/APMonitor-do/blob/master/DynamicOptimization.ipynb

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