Hi,

I have a quick question regarding the bounds on slack constraints. I’m implementing a nlp ocp using python templating, and I have a single nonlinear constraint I’m implementing as a soft constraint on the upper bound. For example:

`0.0 <= h(x,p) `

`h(x,p) - upper_slack_variable <= 10.0`

I understand setting my basic `ocp.constraints.lh / uh`

, (e.g. 0 and 10 here), but I am slightly confused on how I should be setting `ocp.constraints.lsh / ush`

, and what they exactly mean. (I was under the impression that the slack variables would all have built in lower bounds of 0 based on the acados problem formulation, and have no upper bound).

Would I set `ush = 0.0`

, and leave out `lsh`

, to indicate that the slack variable is only on the upper bound? (Along with setting `idxsh = 0`

, since only a single constraint).