Let P be a nonlinear system described byẋ = f (x, u), y = g(x), where the state trajectory x takes values in R n , u and y are scalar and f , g are of class C 1 . We assume that there is a Lipschitz function Ξ : [u min , u max ] → R n such that for every constant input u 0 ∈ [u min , u max ], Ξ(u 0 ) is an exponentially stable equilibrium point of P. We also assume that G(u) = g(Ξ(u)), which is the steady state input-output map of P, is strictly increasing. Denoting y min = G(u min ) and y max = G(u max ), we assume that the reference value r is in (y min , y max ). Our aim is that y should track r, i.e., y → r as t → ∞, while the input of P is only allowed to be in [u min , u max ]. For this, we introduce a variation of the integrator, called the saturating integrator, and connect it in feedback with P in the standard way, with gain k > 0. We show that for any small enough k, the closed-loop system is (locally) exponentially stable around an equilibrium point (Ξ(u r ), u r ), with a "large" region of attraction X T ⊂ R n × [u min , u max ]. When the state (x(t), u(t)) of the closed-loop system converges to (Ξ(u r ), u r ), then the tracking error r − y tends to zero. The compact set X T can be made larger by choosing a larger parameter T > 0, but this may force us to use a smaller k, in which case the response of the system will be slower. Every initial state (x 0 , u 0 ) ∈ R n ×[u min , u max ] such that the state trajectory of P starting from x 0 , with constant input u 0 , converges to Ξ(u 0 ), is contained in some set X T for large enough T . If the open-loop system is globally asymptotically stable, then for every compact subset K of the state space there exists a k > 0 such that all the closed-loop state trajectories starting from K will converge to the unique equilibrium point.