We propose an approach for simultaneous topology identification and synchronization of a complex dynamical network with directed interconnections that relies on the edge-agreement framework and on adaptive-control approaches by design of an auxiliary synchronizing network. Our method guarantees the identification of the unknown directed topology without the need for verifying the Linear Independence Conditions normally required by previous works in the literature. Furthermore, it also guarantees that the complex network reaches synchronization as determined by the internal dynamics of the system. Under our identification algorithm we provide strong stability results for the estimation errors in the form of uniform semiglobal practical asymptotic stability of the estimation errors. Finally, we demonstrate the effectiveness of our approach with a numerical example.

We solve output- and state-consensus problems for multiagent high-order systems in feedback form. We consider systems interconnected over arbitrary (connected) undirected-topology networks as well as directed spanning-trees and directed cycles. We assume that the systems may be subject to multiple restrictions in the form of output or state constraints, such as limited-range measurements and physical limitations. In addition, we suppose that the systems may be subject to external disturbances. Under these conditions, we present a control framework and a formal analysis that establishes robust stability in the input-to-state sense. The former relies on a modified backstepping method and the latter on multistability theory. Finally, we apply our approach to a case-study of interest in the aerospace industry: Safety-aware rendezvous control of underactuated UAVs subject to connectivity and collision-avoidance constraints.

We propose a new method for simultaneous synchronization and topology identification of a complex dynamical network that relies on the edge-agreement framework and on adaptive-control approaches by design of an auxiliary network. Our method guarantees the identification of the unknown topology and it guarantees that once the topology is identified the complex network achieves synchronization. Under our identification algorithm we are able to provide stability results for the estimation errors in the form of uniform semiglobal practical asymptotic stability. Finally, we demonstrate the effectiveness of our approach with an illustrating example.

We address the consensus problem with collision avoidance for multi-agent systems under limited sensing ranges, in the case where new interconnections and agents may be added at any time. The graph topology is represented by a dynamic undirected graph, assumed to be connected only at an initial time, and the open multi-agent system is modeled via a multidimensional impulsive switched representation. We propose a barrier-Lyapunov-function-based consensus control law that guarantees inter-agent collision-avoidance and connectivity maintenance and, relying on the edge-agreement framework, we establish almost-everywhere asymptotic stability of the consensus manifold. The obtained results are also readily applicable to closed multi-agent systems with edge addition. A numerical simulation illustrates the effectiveness of the proposed approach.

We address the agreement-based coordination of first-order multiagent systems interconnected over arbitrary connected undirected graphs and under transient and steady-state constraints. The system is in a leader-follower configuration where only a part of the agents, the leaders, are directly controlled via an external control input, in addition to the agreement protocol. We propose a control law for the leaders, based on the gradient of a potential function, that achieves consensus and guarantees that the trajectories of the inter-agent distances of the entire system remain bounded by a performance function. Relying on the edge-agreement framework and Lyapunov’s first method, we establish strong stability results in the sense of asymptotic stability of the consensus manifold and, in the leaderless case, nonuniform-in-time input-to-state stability with respect to additive disturbances. A numerical simulation illustrates the effectiveness of the proposed approach.

We address the problem of making nonholonomic vehicles, with second-order dynamics and interconnected over a bidirectional network, converge to a formation centered at a nonprespecified point on the plane with a nonprespecified common orientation. We assume that only the Cartesian position of the center of mass of each vehicle and its orientation are available for measurement, but not the velocities. In addition, we assume that the interconnections are affected by time-varying delays. Our control method consists in designing a set of second-order systems that are interconnected with the robots' dynamics through virtual springs and transmit their own coordinates to achieve consensus. This and the virtual elastic couplings with the vehicles make the latter achieve consensus too. To the best of our knowledge, output-feedback consensus control of underactuated nonholonomic vehicles has been little studied, all the less in the presence of delays.

We address the rendezvous control problem of a group of thrust-propelled Unmanned Aerial Vehicles (UAVs) interconnected over an undirected graph and subject to interagent constraints. The proposed distributed control law achieves the desired formation using only local information and guarantees inter-agent collision-avoidance as well as connectivity maintenance. Relying on the edge-agreement framework and on singular-perturbation theory of multi-stable systems we establish almost-everywhere practical input-to-state stability of the desired formation with respect to disturbances. In the absence of perturbations, asymptotic convergence to the consensus manifold is ensured. A numerical simulation illustrates the effectiveness of the proposed approach.

We propose a distributed control law that solves the tracking-in-formation problem for a group of underactuated autonomous marine vehicles interconnected over an undirected graph and subject to inter-agent collision-avoidance and connectivity constraints. The control approach is based on input-output feedback linearization using the so-called hand-position point as the output. Moreover, the control strategy is able to deal with limited knowledge on the target's state and dynamics as well as with disturbances in the form of unknown irrotational ocean currents. We establish almost-everywhere uniform asymptotic stability of the output dynamics with guaranteed respect of the inter-agent constraints. A numerical simulation illustrates the effectiveness of the proposed approach.