<p>This paper investigates the nonparametric estimation problem for some periodic stochastic differential equation driven by fractional <i>G</i>-Brownian motion (fGBm), which generalizes the concepts of the standard Brownian motion, fractional Brownian motion and <i>G</i>-Brownian motion in the framework of sublinear expectation. The fGBm can exhibit long-range dependence and feature the volatility uncertainty simultaneously. Thus it can be a better alternative stochastic process in real applications. First, some probability density function (pdf) called H-<i>G</i>-normal pdf associated with the fGBm is defined, the Volterra representation for fGBm and its Wiener integral are established. Then, the nonparametric estimator for the drift function of the periodic stochastic differential equation is defined by some kernel function, and its consistency and asymptotic distribution are investigated. Finally, some numerical experiments are carried out to illustrate the theoretical results. This study generalizes some well-known existing results of nonparametric estimation.</p>