In the last two decades, research on distributed filtering and control (FAC) has burgeoned into large-scale complex networks and systems. A dis-tributed networked system, typically composed of a number of cost-effective dynamical nodes (agents) with limited sensing, computing, and communication capabilities, is gaining considerable popularity due to its low power consumption, simple installation, high performance, and strong reliability, as compared with the centralized setting. As a result, various network- induced FAC systems, techniques, and algorithms have emerged, including node registration and control, network consensus and synchronization, multi-sensor data clustering/fusion, network topological design and analysis, and the like. In addition, it is important to have an insightful understanding of the way net-works and systems behave and evolve from the FAC perspectives. This is often critical with respect to many important problems, such as managing a limited number of sensors for the best field-of-view coverage, tackling the intrinsic interactions and unknown cor-relations among dynamical nodes, trade-offs between performance and constraints, or achieving automation in noisy environments, just to name a few.