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Data structures and utilities for (rolling horizon) dynamic optimization #2477

Merged
merged 145 commits into from
Nov 4, 2022
Merged

Data structures and utilities for (rolling horizon) dynamic optimization #2477

merged 145 commits into from
Nov 4, 2022

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Robbybp
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@Robbybp Robbybp commented Aug 6, 2022

Summary/Motivation:

I've had some data structures and utilities for dynamic optimization and rolling horizon case studies sitting on my hard drive for a while, and thought it was finally time to clean them up a little, write tests, and commit them somewhere. See the Overview doc page for my motivation for putting together this contrib package. I've found this code useful for MPC case studies, open-loop simulation case studies, and for formulating different kinds of optimal control problems.

Changes proposed in this PR:

  • Add mpc contrib package with data structures, utilities, and an interface class for dynamic optimization
  • Add tests and some documentation

Legal Acknowledgement

By contributing to this software project, I have read the contribution guide and agree to the following terms and conditions for my contribution:

  1. I agree my contributions are submitted under the BSD license.
  2. I represent I am authorized to make the contributions and grant the license. If my employer has rights to intellectual property that includes these contributions, I represent that I have received permission to make contributions and grant the required license on behalf of that employer.

Robbybp added 30 commits July 27, 2022 17:33
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initial documentation for mpc contrib package
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bullet list
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fix code examples
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initial commit of code into contrib.mpc
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more initial commit
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add pyomo boilerplate
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remove pytest marks
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initial commit of new directories
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move dynamic_data/* to data/* and update imports
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remove temp __init__
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move modeling utilities and update import
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move interface files
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rename DynamicModelHelper -> DynamicModelInterface
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tests for constant-setpoint cost
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boilerplate
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initial tests for scalar data
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test __eq__
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move functionality from ScalarData to base class
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remove unused imports
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clarify docstring
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add context arguments
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call pyo.value in to_serializable
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inherit from _DynamicDataBase
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add forgotten context arg
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start testing TimeSeriesData
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tests for SeriesDta
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implement _is_iterable in base class file
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slight refactor and re-add extract_variables
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use common _is_iterable
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some tests for get_cuid
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Robbybp commented Oct 30, 2022

After discussing with @kuanhanl, including on PRs Robbybp#5 and kuanhanl#1, I've made some changes that I think will make this framework more amenable to MHE. These include:

  • Updating the functions in cost_expressions.py and terminal.py to return a set indexing the list of provided variables in addition to the expression, which is now indexed by this set as well as time
  • Updating names of "tracking cost" functions to refer to a generic "penalty" rather than tracking cost

In addition, I've made some API changes that make things somewhat simpler:

  • Remove load_data_from_... methods on DynamicInterface class. Now there is just a single load_data function that automatically decides how to load the data based on its type
  • Add a get_penalty_from_target function and method, which constructs an appropriate quadratic penalty expression depending on the type of data provided for the target

@blnicho blnicho self-requested a review October 31, 2022 16:51
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Robbybp commented Oct 31, 2022

@blnicho Thank you for looking at this thoroughly. I've addressed your comments, and this is ready for re-review.

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Robbybp commented Oct 31, 2022

OSX failure appears unrelated

blnicho
blnicho approved these changes Nov 1, 2022
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@blnicho blnicho merged commit fbd62b4 into Pyomo:main Nov 4, 2022
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@blnicho blnicho blnicho approved these changes

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@Robbybp @blnicho @jsiirola @pyomo-autotest