This paper gives an introduction to the theory of parameter identification and state estimation for system subjected to uncertainties with set-membership bounds on the unknowns. 

The situation under discussion may often turn to be more a propos since here the system and the environment are modeled as truly uncertain rather than noisy. The described approach is purely deterministic. 

On the other hand the techniques involved here for the treatment of system with nonquadratic constraints on the unknowns are proved to have some nontrivial interrelations with those developed in stochastic estimation theory. This may lead to some further estimation schemes that would combine the deterministic and the stochastic models of uncertainty. 

The recurrence procedures of this paper are devised into relations that would allow numerical simulations.