docs(control_performance_analysis): utilize mathjax syntax in readme

[xmfcx]

Description

https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/writing-mathematical-expressions#about-writing-mathematical-expressions

This will sacrifice from the maintainability a bit but make it better and more professional for rendered output.

Rendered beautifully in the documentation page too:
https://autowarefoundation.github.io/autoware.universe/pr-9552/control/control_performance_analysis/#outputs

Related links

Related PR:

• ci(pre-commit): autoupdate #8949

How was this PR tested?

Notes for reviewers

None.

Interface changes

None.

Effects on system behavior

None.

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[github-actions]

Documentation URL: https://autowarefoundation.github.io/autoware.universe/pr-9552/
Modified URLs:

• https://autowarefoundation.github.io/autoware.universe/pr-9552/control/control_performance_analysis/

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 29.50%. Comparing base (e511605) to head (3851485).
Report is 3 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #9552      +/-   ##
==========================================
- Coverage   29.51%   29.50%   -0.01%     
==========================================
  Files        1444     1445       +1     
  Lines      108528   108553      +25     
  Branches    41404    41407       +3     
==========================================
  Hits        32032    32032              
- Misses      73376    73401      +25     
  Partials     3120     3120              

Flag	Coverage Δ		*Carryforward flag
differential	0.00% <ø> (?)
total	29.51% <ø> (ø)		Carriedforward from e511605

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[xmfcx]

Also it is more consistent with the code now with the updated matrix multiplication ordering:

autoware.universe/control/control_performance_analysis/src/control_performance_analysis_core.cpp

Line 221 in 4c0c378

error_vars.error.value_approximation = error_vec.transpose() * lyap_P_ * error_vec; // x'Px

Ready for review ✅

[shmpwk]

COOL!