In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by y_i|(x_i, t_i)∼F(⋅, μ_i) with μ_i=H(η(t_i)+x_i^Tβ), for some known distribution function F and link function H. It is shown that the estimates of β are root-n consistent and asymptotically normal. Through a Monte Carlo study, the performance of these estimators is compared with that of the classical ones.