Feasability checksThe main challenge of the computing discrete equivalents is finding feasible sets of blockable facets and determining whether each facet is controllable. This algorithm does not look for all possible sets of blockable facetes, but instead finds one blockable set with the maximum number of blockable facets for that simplex. It is then checked whether for each facet it can be guaranteed that it is controllable. Blockable setTo find the largest blockable set all combinations of facets are tested starting with all facets blocked. Each tests consist of determining the feasability of the LMI-system consisting of the LMIs limiting the input to the input-polytope and a set of LMIs ensuring that the derivative points inwards, one for each vertex of the facets to be blocked.
Controllable facetsTo determine if a facet is controllable it is necessary to establish weather a fixed point can be avoided in both configurations for the facet (opened and closed). The first check is for the closed configuration, where all facets are
blocked. The fixed point check is done by finding a vector, There are no methods of uniquely finding this vector but at least the outwards normals to the blocked facets will not yield a result, and neither will convex combinations of them. As testvectors both the inwards and outwards normals to the facets are chosen as a feasible result will mean that the vector field in general points away from or towards one of the facets. If no control can be found which ensures fixed points outside the simplex the blockable set is no good and must be thrown away. Given that the closed configuration is feasible it needs to be established whether the individual facets are controllable. This is done by using the LMI system used for establising
blockability, but reversing the derivative requirement on the facet
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