Heterogeneous Multi-agent Systems Research Articles

Distributed adaptive finite-time fault-tolerant cooperative control of heterogeneous multi-agent systems with saturation and disturbances

In this paper, the issue of distributed adaptive finite-time fault-tolerant cooperative control (FT-FTCC) problem is investigated for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with unknown parameter uncertainties, actuator faults, input saturation and external disturbances. Starting from the dynamic models of the UAVs and UGVs, an unified control model is presented. Then, a sliding-mode estimator is presented to estimate the position of the leader for the followers which only uses the information from neighbours. Next, a distributed adaptive FT-FTCC scheme, which can also deal with the uncertainties, actuator faults, input saturation and disturbances, is proposed by utilising disturbance observers and neural networks. Based on Lyapunov function approach, the tracking errors of all followers subject to the pre-defined desired positions are uniformly ultimately bounded. Finally, simulations are given to validate the efficiency of the developed FT-FTCC scheme.

Consensus analysis for heterogeneous multiagent systems subject to input saturation

AbstractThis paper investigates the consensus problem of heterogeneous multiagent systems (HMASs) consisting of first‐order and second‐order agents, where second‐order linear and second‐order nonlinear agents are included in the second‐order agents. Firstly, the consensus problem of HMASs without input saturation is studied in the first part. However, in practical applications, due to the physical limitations of actuators, saturation often occurs. Therefore, we focus on the consensus problem of HMASs with input saturation in the second part. Then based on the knowledge of Lyapunov stability theory and graph theory, it gives sufficient conditions for these HMASs to reach consensus, which ensures that each agent eventually reaches consensus. Eventually, the effectiveness of the theory is verified by performing simulations.

Double adaptive event-triggered strategy for leader-following group consensus of heterogeneous multi-agent systems in cooperative–competitive networks

This article investigates adaptive event-triggered control for leader-following group consensus of hybrid heterogeneous multi-agent systems (HMASs) composed of single- and double-integrator agents under cooperative–competitive relationships. By using fully distributed control protocol and adaptive protocol, the leader-following group consensus can be achieved without global information. Additionally, a novel adaptive double dynamic event-triggered mechanism (DDETM) is proposed, in which two independent adaptive event-triggered conditions are devised to maintain events of communication and updates of controllers. Furthermore, adaptive parameters and internal dynamic variables are employed to reduce the number of triggers and exclude Zeno phenomenon. By utilizing Lyapunov stability theory, some sufficient conditions are acquired for the leader-following group consensus of the HMASs. Finally, simulation examples are given to prove the effectiveness of the proposed method.

Adaptive fault-tolerant containment control for heterogeneous uncertain nonlinear multi-agent systems under actuator faults

As modern control systems involve a growing number of actuators, the consequent number of faults occurrence, which may deteriorate the closed-loop system performance, is increasing. Focusing on the containment control problem of generic nonlinear high-order heterogeneous uncertain Multi-Agent Systems, this study proposes a novel distributed adaptive fault-tolerant Proportional-Integral-Derivative control protocol to improve the reliability and the resilience of the whole networked systems against actuator failures. The Lyapunov theory, combined with the Barbalat lemma, provides the design of suitable adaptive mechanisms that adjust the PID control actions to ensure the asymptotic convergence of the closed-loop containment errors for the overall network, hence implying the convergence of each agent state toward the convex region shaped by the multiple leaders, despite the occurrence of actuators faults. The fulfillment of the fault-tolerant containment objective is ensured by requiring a lower computational burden with respect to alternative solutions, hence resulting in more attractive for wider practical engineering applications. Numerical simulation results, also including a comparison analysis with a state-of-the-art controller, corroborate the efficiency and the advantages of the proposed distributed PID controller.

Consensus tracking control of heterogeneous nonlinear multi-agent systems with random switching and uncertain targets

Consensus tracking control of heterogeneous nonlinear multi-agent systems with random switching and uncertain targets

Reinforcement Learning for Synchronization of Heterogeneous Multiagent Systems by Improved Q-Functions.

This article dedicates to investigating a methodology for enhancing adaptability to environmental changes of reinforcement learning (RL) techniques with data efficiency, by which a joint control protocol is learned using only data for multiagent systems (MASs). Thus, all followers are able to synchronize themselves with the leader and minimize their individual performance. To this end, an optimal synchronization problem of heterogeneous MASs is first formulated, and then an arbitration RL mechanism is developed for well addressing key challenges faced by the current RL techniques, that is, insufficient data and environmental changes. In the developed mechanism, an improved Q-function with an arbitration factor is designed for accommodating the fact that control protocols tend to be made by historic experiences and instinctive decision-making, such that the degree of control over agents' behaviors can be adaptively allocated by on-policy and off-policy RL techniques for the optimal multiagent synchronization problem. Finally, an arbitration RL algorithm with critic-only neural networks is proposed, and theoretical analysis and proofs of synchronization and performance optimality are provided. Simulation results verify the effectiveness of the proposed method.

Distributed Cooperative Control of Heterogeneous Multiagent Systems for Air‐to‐Ground Formation

ABSTRACTThis paper is concerned with a distributed cooperative formation problem for a heterogeneous multiagent system with a car‐like mobile robot, a quadrotor, and an omnidirectional wheeled mobile robot. In the heterogeneous multiagent system, a three‐layer distributed cooperative formation control strategy is constructed to achieve air‐to‐ground formation, the car‐like mobile robot tracks a virtual leader, the quadrotor, and the omnidirectional wheeled mobile robot track the car‐like mobile robot. Two nonlinear leader‐follower controllers based on exponential virtual control laws are designed to maintain formation for the quadrotor and the omnidirectional wheeled mobile robot. A kinematics controller with continuous functions, an improved adaptive sliding mode controller and a suitable back‐stepping controller are introduced in the heterogeneous multiagent system, respectively. Multiagent communication is one of the key steps to accomplish multiagent time synchronization. Experimental results are given to illustrate the applicability of the proposed distributed cooperative control strategy.

Event-triggered bipartite consensus to heterogeneous multiagent systems under DoS attacks: A fully distributed method

This paper studies event-triggered bipartite output consensus problem of heterogeneous multiagent systems under denial-of-service (DoS) attacks. A novel dynamic event-triggered scheme (DETS) is proposed, which, by introducing an extra dynamic function with time-varying coefficients into triggering conditions, can guarantee strictly positive minimum inter-event intervals no matter DoS attacks occur or not. An event-based resilient compensator with adaptive coupling coefficients is then designed to estimate leader's state, and a hybrid model with jump dynamics is constructed that can incorporate the estimation error, DETS, and DoS attacks, and is useful for convergence analysis. Then, a fully distributed observer-based control protocol is designed to regulate the bipartite output consensus. The main advantages of the proposed method include: 1) global information is not needed to implement the event-based control protocol; 2) strictly positive inter-event intervals are guaranteed even under DoS attacks. Finally, a numerical example is presented to testify the main results.

Finite-Time Pinning Event-Triggered Control for Bipartite Consensus of Hybrid-Order Heterogeneous Multi-Agent Systems with Antagonistic Links

Finite-Time Pinning Event-Triggered Control for Bipartite Consensus of Hybrid-Order Heterogeneous Multi-Agent Systems with Antagonistic Links

Resilient consensus of heterogeneous multi-agent systems under asynchronous optimal DoS attack schedules

This study aims to address the challenge of achieving resilient consensus in heterogeneous multi-agent systems (MASs) under asynchronous optimal Denial of Service (DoS) attack schedules. Considering the start and duration of adversaries vary from different communication channels of MASs, we mainly focus on how adversaries with limited energy choose channels to launch attacks to cause the greatest damage to system performance. Based on dynamic programming, an asynchronous optimal DoS attack schedules generation algorithm is obtained. Optimal DoS attack schedules provides a basis for designing more effective secure control methods. Then, a distributed resilient control strategy that utilizes an observer-based approach to achieve output consensus in heterogeneous MASs under asynchronous optimal DoS attack schedules is proposed. Additionally, we establish conditions regarding the durations and frequencies of DoS attacks as well. Finally, two simulations are performed to showcase the efficacy of our proposed method.

Model-free adaptive consensus design for a class of unknown heterogeneous nonlinear multi-agent systems with packet dropouts

This paper studies the consensus problem for a class of unknown heterogeneous nonlinear multi-agent systems via a network with random packet dropouts. Based on the dynamic linearization technique, novel model-free adaptive consensus protocols with the data compensation mechanism are designed for both leaderless and leader-following cases. The advantage of this approach is that only neighborhood input and output data of the agents are required in the protocol design. For the stability analysis, a new Squeeze Theorem based method is developed to derive the theoretic results instead of the traditional contraction mapping principle used in model-free adaptive control. It is shown that the consensus can be achieved for both leaderless and leader-following cases if the communication topology is strongly connected. Finally, numerical simulations verifying the correctness of the theoretical results are given.

Robust Predefined Output Containment for Heterogeneous Nonlinear Multiagent Systems Under Unknown Nonidentical Leaders' Dynamics.

This article discusses the robust predefined output containment (RPOC) control problem for heterogeneous nonlinear multiagent systems having multiple uncertain nonidentical leaders. In order to solve this problem, a new kind of distributed observer-based RPOC control framework is presented. First, for obtaining the information of nonidentical leaders' dynamics, including uncertain parameters in leaders' system matrices, output matrices, states, and outputs, four kinds of adaptive observers are constructed in a fully distributed form without any knowledge of the dynamics of nonidentical leaders, exactly. Second, on the basis of adaptive learning technique, a new RPOC controller is then developed by using the presented observers, where the adaptive observers can make up for the uncertain parameter in followers' dynamics, and the solutions of output regulation equations can be obtained adaptively by the developed adaptive strategy. Furthermore, with the help of the output regulation method and Lyapunov stability theory, the RPOC criteria for the considered system under unknown nonidentical leaders' dynamics are derived from the constructed controller. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed RPOC controller.

Mixed-Zero-Sum-Game-Based Memory Event-Triggered Cooperative Control of Heterogeneous MASs Against DoS Attacks.

This article studies the problem of memory event-triggered cooperative adaptive control of heterogeneous nonlinear multiagent systems (MASs) under denial-of-service (DoS) attacks based on the multiplayer mixed zero-sum (ZS) game strategy. First, a neural-network-based reinforcement learning scheme is structured to obtain the Nash equilibrium solution of the proposed multiplayer mixed ZS game scheme. Then, a memory-based event-triggered mechanism considering the historical data is proposed. This effectively avoids incorrect triggering information caused by unknown external factors. Moreover, thanks to the idea of switching topology, the mixed ZS game problem under the influence of node-based DoS attacks is solved efficiently. In accordance with the Lyapunov stability theory, it is proved that all signals of heterogeneous MASs are bounded, all heterogeneous followers can track the trajectory of the leader during the no-attack period, the attacked follower can achieve stabilization control during the attack period, and the remaining nonattacked followers can achieve cooperative control during the attack period. Finally, the effectiveness of the designed memory-event-triggered-based mixed ZS game cooperative control strategy is tested by the given simulation results.

Guest Editorial Special Issue on Robust Cooperative Control for Heterogeneous Nonlinear Multiagent Systems

Guest Editorial Special Issue on Robust Cooperative Control for Heterogeneous Nonlinear Multiagent Systems

Distributed Prescribed-Time Consensus Tracking for Heterogeneous Nonlinear Multi-Agent Systems Under Deception Attacks and Actuator Faults

Distributed Prescribed-Time Consensus Tracking for Heterogeneous Nonlinear Multi-Agent Systems Under Deception Attacks and Actuator Faults

Bipartite Fixed-time Output Consensus of Singular Heterogeneous Linear Multi-agent Systems Under Directed Signed Topology

Bipartite Fixed-time Output Consensus of Singular Heterogeneous Linear Multi-agent Systems Under Directed Signed Topology

Rigid Formation Control on a Sphere: A Heterogeneous System Approach.

We consider a heterogeneous multiagent system for tracking multiple targets with a rigid formation on a unit sphere, where the targets and chasing agents are governed by single- and double-integrator models, respectively. To make asymptotic rendezvous between agents and their corresponding targets, we use an autonomous system consisting of attraction forces and velocity alignments. If the target's position, velocity, and acceleration information are available, we derive a multiagent system for complete rendezvous and obtain its exponential convergence result. If we have only the location and velocity information of the targets, we provide an autonomous system for practical rendezvous and the corresponding mathematical analysis. To prove the main results, we employ frame-rotation-structure decomposition for the double-integrator model and the geometric properties of a rigid formation on a sphere. We also provide numerical simulations to confirm our mathematical results and apply them to multiagent dynamics with a rigid formation that patrols the boundary line for a certain area on the sphere.

Collision-Free Formation Control for Heterogeneous Multiagent Systems Under DoS Attacks.

A safe time-varying formation (TVF) control framework is proposed in this article for heterogeneous multiagent systems under the constraints of denial of service (DoS) attacks, noncooperative dynamic obstacles, and input saturation. The framework integrates both the cyber-layer and physical-layer components to address the challenges posed by these adverse conditions. In the cyber-layer, a distributed resilient observer is provided based on a control Lyapunov function (CLF)-quadratic program (QP). This observer estimates a reference exosystem, effectively decoupling heterogeneous dynamics from unsafe networks and optimizing the system resilience against DoS attacks. At the physical-layer, for the first time, a collision-free TVF controller is presented based on the CLF-exponential control barrier function-QP. The controller guarantees high-order heterogeneous agents' operation safety under noncooperative obstacles and input saturation. The effectiveness and advantages of the proposed algorithms are verified through the comparative simulations and experiments conducted on a physical system comprising unmanned aerial vehicles and unmanned ground vehicles.

Robust Formation Tracking Control for Noncooperative Heterogeneous Multiagent Systems.

The robust formation tracking problems (FTPs) are investigated for noncooperative heterogeneous multiagent systems (MASs). The parameters and state dimensions of each agent in the MASs can be heterogeneous. The leader is noncooperative and has an unknown external input. The followers are affected by uncertainties and disturbances. A distributed extended state observer is designed to estimate the leader's state and the unknown external input. Then a robust formation tracking control method is proposed. It turns out that the output formation tracking error can reduce to any size neighborhood near the origin by selecting appropriate parameters. Finally, the effectiveness of the proposed observer and controller is demonstrated by a numerical simulation example and a hardware-in-the-loop (HITL) simulation example.

Event-triggered distributed consensus control of heterogeneous multi-agent system under communication and actuator faults

In this paper, a heterogeneous leader-follower multi-agent system is studied under simultaneous time-varying communication faults and actuator faults. First, the state of the leader is modeled as the closed-loop reference model (CRM) where the states of the direct-connected followers are fed to the leader to improve the leader-follower tracking capability. An event-triggered communication mechanism is designed for the agent information sharing among its neighbors so as to reduce the communication burden. The designed event-triggered mechanism, capable of adjusting the triggering interval threshold within a certain range, can be applied in practical multi-robot collaborative control to accommodate the varying requirements for different triggering intervals. Considering the time-varying communication link failures, a new distributed event-triggered observer is designed for each follower to estimate the system states so as to reduce the state error, whereas the adaptive distributed event-triggered estimators are further designed for the non-directly connected followers to estimate the coefficient matrix of the leader system. Then, an estimator is designed for the actuator fault estimation to mitigate their impact on the system consistency. Finally, an adaptive control strategy is proposed to ensure the consistency of the leader-follower system under the time-varying communication link faults and actuator faults. It is also shown that Zeno behavior is excluded for each agent and the effectiveness of the proposed adaptive event-triggered control strategy is verified on a heterogeneous multi-agent system.