A Fast Row-Stochastic Decentralized Method for Distributed Optimization Over Directed Graphs

This paper considers the consensus control problem of heterogeneous linear multiagent systems. A distributed proportional-integral (PI) protocol is presented to ensure consensus of heterogeneous linear multiagent systems with directed communication graphs. Sufficient conditions for the choice of control parameters are derived. For the case that the agents are subject to the external time-varying but bounded disturbances, the proposed distributed PI protocol can assure uniformly ultimate boundedness of the consensus error. The effectiveness of the results is illustrated both theoretically and numerically.

This paper presents an event‐triggered distributed control protocol designed for scenarios involving Denial‐of‐Service (DoS) attacks within directed communication graphs. We address the consensus problem of uncertain systems by employing neural networks to approximate nonlinear components. Compared with traditional neural network observers, the proposed method incorporates damping terms to ensure the boundedness of neural network estimators. Initially, an auxiliary system was constructed to decouple the consensus problem under a directed communication graph framework. It is demonstrated that the uncertain nonlinear system can achieve consensus through the utilization of information exchanged among neighboring agents. Subsequently, to curtail the consumption of communication resources, we introduce an event‐triggered control protocol based on the aforementioned approach, incorporating an effective event‐triggering function. Building upon the proposed control protocol, we further develop a control strategy tailored for systems under DoS attacks. Furthermore, the event‐triggered mechanism without using global information in trigger condition not only curtails superfluous information exchange among agents but also precludes the occurrence of Zeno behavior (i.e., infinite triggering within a finite time interval). Finally, numerical simulations are carried out to validate the efficacy of the proposed control protocol.

This paper considers the distributed consensus disturbance rejection problem for general linear multiagent systems with deterministic disturbances under directed communication graphs. Based on the relative state information of the neighboring agents, the consensus protocols, which consist of two observers, including a state observer and a separate disturbance observer, are designed to guarantee that the consensus error goes to zero with complete disturbance rejection. Furthermore, the state observer is designed in a fully distributed fashion with adaptive coupling gain, which has the advantage that the consensus controller design is independent of the Laplacian matrix associated with the communication network. The distributed observer-based consensus disturbance rejection protocols are further extended to containment control. Finally, an example is provided to demonstrate the effectiveness of the proposed strategies.

This paper addresses the distributed consensus protocol design problem for multi-agent systems with general linear dynamics and directed communication graphs. Existing works usually design consensus protocols using the smallest real part of the nonzero eigenvalues of the Laplacian matrix associated with the communication graph, which however is global information. In this paper, based on only the agent dynamics and the relative states of neighboring agents, a distributed adaptive consensus protocol is designed to achieve leader-follower consensus for any communication graph containing a directed spanning tree with the leader as the root node. The proposed adaptive protocol is independent of any global information of the communication graph and thereby is fully distributed. Extensions to the case with multiple leaders are further studied.

This paper deals with a cooperative control problem of a team of double-integrator agents moving along a set of given curves with a nominated formation. A projection-tracking design method is proposed for designing the path-following control and the formation protocol, which guarantee formation motion of the multi-agent system under a directed communication graph. Necessary and sufficient conditions of the control gains for solving the coordinated problem are obtained when the directed communication graph has a globally reachable node. Simulation results of formation motion among three agents demonstrate the effectiveness of the proposed approach.

This paper studies the adaptive consensus tracking problem for multi-agent systems modeled as high-order integrators with uncertain nonlinear dynamics under directed communication graphs. By parameterizing the unknown dynamics of the agents and the unknown input of the leader, two decentralized tracking control laws are designed using the state information and only the output information, respectively. With state information, globally uniformly ultimately bounded consensus tracking with arbitrarily small tracking errors can be achieved and when only output information is available, based on high-gain observers, semi-global result can be obtained. Numerical examples are provided to illustrate the effectiveness of the controllers.

Robust finite-time containment control of general linear multi-agent systems under directed communication graphs

In this paper, consensus tracking for a class of second-order nonlinear multi-agent systems with a dynamic leader under general directed communication graphs is considered. Only relative output measurements are assumed to be available for each agent. Based on a distributed observer design, global consensus tracking controller using only relative output information is proposed. Sufficient conditions on the controller parameters are derived to ensure consensus tracking. A simulation example is provided to illustrate the effectiveness of the proposed controller.

In vehicular networks, drones can enhance performance by enabling real-time data collection, traffic monitoring, and communication optimization. However, due to the large, open, and highly dynamic nature of vehicular networks, ensuring security and achieving lightweight privacy protection are pressing challenges. Additionally, in traditional solutions, the control center (CC) often performs many tasks, leading to excessive computation and communication overhead, creating a system bottleneck. To address these issues, this paper proposes a privacy-preserving authentication scheme for FL in drone-assisted vehicular networks, where model parameter collection and model training are performed by drones in a privacy-preserving manner, significantly reducing the computation and communication overhead on the CC side. Moreover, the proposed scheme ensures strong privacy protection and efficient authentication by using federated learning, Elliptic Curve Cryptography (ECC), and the Chinese Remainder Theorem (CRT). The performance evaluation results show that the proposed scheme achieves a 17.3% reduction in computation overhead and a 22.8% reduction in communication overhead compared to existing solutions, highlighting its significant advantages.

In this article, the containment control problem of multiagent systems (MASs) with active leaders under a directed communication graph is addressed. A novel pull-based event-triggered protocol combined with aperiodic sampled-data mechanism is first presented, where each agent merely updates controller at its own triggering instants. Under the proposed control protocols, the information is only exchanged and calculated at the aperiodic sampling instants, therefore, it can reduce communication congestion and save computing resources. Furthermore, the Zeno behavior is naturally excluded because the trigger instants are in the set of aperiodic sampled instants. By virtue of the algebraic graph theory and Lyapunov stability analysis, it is shown that the active leaders can reach their desired states predefined arbitrarily and all followers are driven to the convex hull formed by the leaders. Finally, an illustrative example is given to validate the theoretical results and emphasize the advantages of the proposed protocols.

Robust consensus of uncertain linear multi-agent systems via dynamic output feedback

This paper focuses on the control of a team of agents designated either as leaders or followers and exchanging information over a directed communication network. The goal is to drive each follower to a target position that depends on its neighbors. To this purpose, we propose a decentralized control scheme based on sliding-mode techniques and study the position error propagation within the network using the notion of Input-to-State Stability (ISS). In particular, we derive sufficient conditions on the control parameters for guaranteeing that the error dynamics is ISS with respect to the leaders' velocities. Moreover, we show that, under suitable assumptions, the sliding-mode part of the control law is capable of steering the position errors to zero in finite time. The theoretical results are backed up by numerical simulations.

In this article, the asymptotic tracking consensus problem of higher-order multiagent systems (MASs) with general directed communication graphs is addressed via designing event-triggered control strategies. One common assumption utilized in most existing results on such tracking consensus problem that the inherent dynamics of the leader are the same as those of the followers is removed in this article. In particular, two cases that the dynamics of the leader are subjected, respectively, to bounded input and unknown nonlinearity are considered. To do this, distributed event-triggered observers are first constructed to estimate the state information of the leader. Then, local event-triggered tracking control protocols are designed for each follower to complete the goal of tracking consensus. One distinguishing feature of the present distributed observers lies in the fact that they could avoid the continuous monitoring for the states of the neighbors' observer states. It is also worth pointing out that the present tracking consensus control strategies are fully distributed as no global information related to the directed communication graph is involved in designing the strategies. Two simulation examples are finally presented to verify the efficiency of the theoretical results.

By applying iterative learning control approach, the consensus is studied for multi‐agent systems (MASs) with one‐sided Lipschitz (OSL) nonlinearity. Firstly, the P‐type and D‐type learning schemes with initial state learning are introduced for such MASs. Then, utilizing the OSL and the quadratically inner‐bounded constraints, the convergence conditions of the consensus algorithms are presented and analyzed under a directed communication graph. We show that both algorithms, on a fixed finite‐time interval, can achieve perfect consensus tracking. Finally, the correctness of the obtained results is illustrated with simulation examples.

This paper deals with the consensus tracking problem for a multiagent system with nonholonomic chained-form dynamics. A new distributed observer is first proposed for each follower to estimate the leader state and the leader input in a prescribed finite-time under both undirected and directed communication graphs. Then based on the observer and by adding a power integrator, a novel nonlinear protocol is designed such that the estimated leader state is tracked in a prescribed finite-time. Different from some existing finite-time consensus tracking approaches, an explicit bound without dependence on initial states is derived for the settling time. Therefore, in an unknown environment where initial conditions are unavailable, the proposed strategy is able to meet specific system requirements, e.g., a military target is tracked by a group of field robots in a prescribed time. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed protocol.