Dynamic Topology Inference via External Observation for MultiRobot Formation Control Network communication topology through which robots achieve intelligent collaboration in multirobot formation control systems is of fundamental importance. Existing works focusing on security issues of multirobot systems usually assume that the topology is priori knowledge. However, the topology graph is not accessible for inner security policies or ID identification from the outside of the system. An intriguing question is how to construct the communication topology via observation from the outside point of view. This work studies the problem of constructing topology graph that represents magnitude of robots interaction via observing trajectories. The main novelties of this work include: i) It is the first time to consider the topology inference problem in multirobot formation control systems. ii) We transform the inference issue into a linear regression problem. The optimal estimation of Perron matrix that contains the interaction profile is derived using l 2 norm least square algorithm (l 2 LS). iii) Considering the link failure and creation, we propose a novel dynamic window least square algorithm (DWLS) to identify dynamic changing topology. Finally, simulation results demonstrate that l 2 LS has 95% inference accuracy averagely when noise parameter xcexbc  0.05, and DWLS is robust and stable in identifying time slices, moreover, accuracy approaches 90%.

Leaderfollowing consensus of linear timevarying multiagent systems under fixed and switching topologies Abstract   The leaderfollowing consensus problems for linear timevarying multiagent systems under fixed and switching topologies are considered. Several results are derived on the basis of Lyapunovxe2x80x99s direct method. For a network of linear timevarying agents with fixed topology, we provide two protocols, respectively. One of them uses global information of the communication topology. It guarantees the multiagent system to go to the leaderfollowing agreement with an arbitrarily given exponential rate. The other uses local information associated with each follower, and is implemented in a fully distributed fashion. It has robustness with respect to a certain degree of link failure. It is extended to a network of linear timevarying agents with switching topology. The resulting protocol guarantees the multiagent system to achieve the leaderfollowing consensus, if the union of switching graphs has a spanning tree rooted at the leader. It also has robustness with respect to a certain degree of link failure. Simulation examples are provided to validate the effectiveness of the results.