"Spatially distributed multi-agent networks have been used successfully to model a wide range of natural, social and engineered complex systems, such as animal groups, online communities and electric power grids. In various contexts, it is crucial to introduce control actions into such networks to either achieve desired collective dynamics or test the understanding of the systems’ behavior. However, controlling such systems is extremely challenging due to agents’ complicated sensing, communication and control interactions that are distributed in space. Systematic methodologies to attack this challenge are in urgent need, especially when vast efforts are being made in multiple disciplines to apply the model of complex multi-agent networks.The goal of the project is twofold. First, understand whether a complex multi-agent network can be controlled effectively when the agents can only sense and communicate locally. Second, provide methodologies to implement distributed control in typical spatially distributed complex multi-agent networks. The project requires integrated skills since both rigorous theoretical analysis and novel empirical explorations are necessary.The research methods that I plan to adopt have two distinguishing features. First, I use tools from algebraic graph theory and complex network theory to investigate the impact of network topologies on the systems’ controller performances characterized by mathematical control theory. Second, I utilize a homemade robotic-fish testbed to implement various multi-agent control algorithms. The unique combination of theoretical and empirical studies is expected to lead to breakthroughs in developing an integrated set of principles and techniques to control effectively spatially distributed multi-agent networks. The expected results will make original contributions to control engineering and robotics, and inspire innovative research methods in theoretical biology and theoretical sociology."