In this paper, the complete moment convergence for the partial sums of moving average processes $\{X_n=\sum_{i=-\infty}^{\infty}a_iY_{i+n},n\ge 1\}$ is proved under some proper conditions, where $\{Y_i,-\infty<i<\infty\}$ is a doubly sequence of identically distributed, negatively dependent random variables under sub-linear expectations and $\{a_i,-\infty<i<\infty\}$ is an absolutely summable sequence of real numbers. The results established in sub-linear expectation spaces generalize the corresponding ones in probability space.