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Update benchmarks to help with optimal control tuning#800

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murrayrm merged 5 commits intopython-control:mainfrommurrayrm:benchmarks-24Aug2022
Nov 26, 2022

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murrayrm
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This PR updates the benchmarks to allow for more useful characterization and tuning of theoptimal module. The main change is to switch from using the kinematic car (vehicle) example as the basis for benchmarking to using a simpler linear system. The kinematic car was problematic because it is a marginally stable system and so the shooting method using for the optimal control computations was not numerically stable, causing lots of failures.

Almost all of the changes here are in the benchmarks/ directory, with a few small changes in the main code to fix some small issues identified along the way.

Once this PR and#799 are merged, I'll add some benchmarks comparing the shooting method to collocation.

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Coverage Status

Coverage increased (+0.002%) to 94.842% when pulling54de2a3 on murrayrm:benchmarks-24Aug2022 into832527d on python-control:main.

@murrayrmmurrayrm merged commit4d89991 intopython-control:mainNov 26, 2022
@murrayrmmurrayrm added this to the0.9.3 milestoneDec 24, 2022
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