Add B-splines and solve_flat_ocp to flatsys #763
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* add initial_guess functionality to solve_flat_ocp * pre-compute collocation matrices in point_to_point, solve_flat_ocp * updated return values for solve_flat_ocp * add __repr__ for flat basis functions * docstring improvements * additional unit tests + examples
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Merging this in since the functionality is pretty specialized and so not something that is going to break anything for others (plus I have additional updates coming that build on this one). |
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Hi @murrayrm, I started to look through it a few days ago but wasn't done completely. I might have a few review comments later on, if that is okay. |
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Thanks for looking through this, @bnavigator. Comments are definitely welcome and I'm happy to address in a separate PR. I'm working in putting some numba capability into python-control to allow for more efficient optimization, and this PR was in support of that. The changes are very specialized, so won't affect 99% of users (and perhaps 99.9% of users -:). |
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This PR extends the
flatsysmodule to include two new elements:flatsys.BSplineFamilyadds B-splines as a new type of basis for solving trajectory generation problems (withinflatsysoroptimal).flatsys.solve_flat_ocp()allows solution of optimal control problems for differentially flat systems with trajectory and terminal costs and constraints, mirroring the functionality ofoptimal.solve_ocp().In the process of making these additions, a few other changes:
flatsys.BSplineFamilyintroduces the ability to have multi-variable basis functions (where each flat output uses a different basis function from a selected family). This is useful if you have a differentially flat system in which you would like to have different degrees for different variables.__repr__for basis functions (show the family + information on attributes).