In aerial reconfigurable intelligent surface (RIS) aided networks, high line-of-sight (LoS) and agility characteristics provide favorable conditions for RIS reflection. However, this also introduces extra LoS RIS reflection interference, especially when aerial RIS is fixedly deployed. This paper proposes a dynamic unmanned aerial vehicle (UAV)-mounted RIS aided multi-cell multi-user communication scheme, where the minimum ergodic rate of randomly mobile users is maximized through joint optimization of BS beamforming, RIS phases, user scheduling and UAV trajectory under the assumption of only statistical channel state information. Specifically, a closed-form ergodic rate approximation is derived, based on which the block coordinate descent framework is leveraged to solve the above four variables due to the non-convexity of the problem. Furthermore, the optimal beamforming is acquired in closed form utilizing fractional programming and quadratic transformation, RIS phases are optimized by the complex circle manifold, user scheduling is obtained by the reconstruction-based relaxation, and UAV trajectory is solved through the first-order Taylor expansion and successive convex optimization techniques. Moreover, the complexity of the proposed algorithm is analyzed and its convergence is carefully proved. The numerical results demonstrate our proposed scheme achieves a better ergodic rate than traditional methods and other aerial schemes with heuristic trajectories.