“…Here, given our focus on estimation, we assume that the system variables are divided into measured variables, to-be-estimated variables and, possibly, disturbances (which play the role of unknown inputs in the classical approach). To investigate the behavioral estimation problem, we rely on the behavioral theory of observers introduced in [11] and [10], as well as on our previous results on conditioned invariant and behavioral detectability subspaces presented in [12]. Roughly speaking, an observer for a given behavior B is a second behavior B that shares the measured variables with B and produces a suitable estimate of the to-beestimated variables, in the sense that the error behavior (i.e., the set of all estimation error signals) has certain desired properties, see Figure 1: On the other hand, conditioned invariant and detectability subspaces are behaviors V e contained in the error behavior B e of an observer, such that the quotient behavior B e /V e has suitable properties: specifically, autonomy and stability.…”