The purpose of this note is two-fold. Firstly we deal with projected dynamical systems that recently have been introduced and investigated in finite dimensions to treat various time dependent (dis)equilibrium and network problems in operations research. Here at the more general level of a Hilbert
space, we show that a projected dynamical system is equivalent in finding the “slow” solution (the solution of minimal norm) of a differential variational inequality, a class of evolution inclusions studied much earlier. This equivalence follows easily from a precise geometric description of the directional derivative of the metric projection in Hilbert space. By our approach, we can easily characterize a stationary point of a projected dynamical system as a solution of a related variational inequality.
Secondly we are concerned with stability of the solution set to differential variational inequalities. Here we present a novel upper set convergence result with respect to perturbations in the data. In particular, we admit perturbations
of the associated set-valued maps and the constraint set, where we impose weak convergence assumptions on the perturbed set-valued maps and employ Mosco convergence as set convergence.