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Math formulation about orca HOT 1 OPEN

ahoarau avatar ahoarau commented on September 28, 2024
Math formulation

from orca.

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iadev avatar iadev commented on September 28, 2024

This formulation is fine, but maybe we can make it otherwise.

Another way to put it is IMHO to take linear constraints, i.e. E.x = f, as the "base" construction object for both tasks and constraints (ignoring the case of inequality constraints for this discussion).
Then an objective can be associated to this constraint, e.g. || E.x - f ||^2.
The advantage is twofold:

  • we do not have confusing "minus" signs everywhere;
  • we can easily transform any constraint into a task (might be useful for control purposes).

Actually we might have something like functions, constraints on functions, and metrics on constraints:

  • [Function, y := foo(x)] <-- [Linear function, y := E.x]
  • [Ineq constraint, c := y - f < 0] , [Equality constraint, c := y - f = 0]
  • [Square eq constraint norm, || c ||^2]
    (- [Square ineq constraint norm, || c ||^2 if c > 0, 0 otherwise])

A classic quadratic task would then be a "square equality constraint norm" on an "equality constraint".
At any point in time we could convert this task into a constraint if needed, and vice-versa.
That would be useful also to transition on equality constraints activation by creating a task on it temporarily.

Note: this moves the question to whether y = f or y = 0 is the proper way to write an equality constraint. In the former we only need linear functions y := E.x, in the latter affine functions y := Ex +/- f...

from orca.

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