Controlled mobile helper nodes called data ferries have recently been proposed to bridge communications between disconnected nodes in a delay-tolerant manner. While existing work has explored various trajectory designs for the data ferry by assuming either static nodes or full observations at the data ferry, the problem remains open when the nodes are mobile and the ferry only has partial observations. In this paper, we investigate the problem of dynamic ferry mobility control under limited-range sensing. Assuming the data ferries are capable of sensing node presence within certain range and adjust their movements dynamically, we aim to design control policies that maximize the number of effective contacts. We provide a comprehensive model of the control framework using Partially Observable Markov Decision Process (POMDP), based on which we study the structure of the optimal policy and propose an efficient heuristic policy which shows significant improvement over the predetermined benchmark. To the best of our knowledge, this is the first data ferry control mechanism that can handle both stochastic node mobility and incomplete ferry observations.