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Yes if the context, the list of variables defining the motion controlproblem, is dimensionally similar. Here we show that by modifying the problemformulation using dimensionless variables, we can re-use the optimal controllaw generated numerically for a specific system to a sub-space of dimensionallysimilar systems. This is demonstrated, with numerically generated optimalcontrollers, for the classic motion control problem of swinging-up atorque-limited inverted pendulum. We also discuss the concept of regime, aregion in the space of context variables, that can help relax the condition ondimensional similarity. Futhermore, we discuss how applying dimensionnalscaling of the input and output of a context-specific policy is equivalent tosubstituing the new systems parameters in an analytical equation fordimentionnaly similar systems. It remains to be seen if this approach can alsohelp generalizing policies for more complex high-dimensional problems.

Dimensionless Policies based on the Buckingham $\pi$ Theorem: Is it a good way to Generalize Numerical Results?