Heterogeneous Multi-agent Systems Research Articles

Neural Network-Based Fixed-Time Tracking and Containment Control of Second-Order Heterogeneous Nonlinear Multiagent Systems.

This study concentrates on the fixed-time tracking consensus and containment control of second-order heterogeneous nonlinear multiagent systems (MASs) with and without measurable velocity under directed topology. By defining a time-varying scaling function and approximating the unknown nonlinear dynamics with radial basis function neural networks (RBFNNs), a novel distributed protocol for solving the fixed-time tracking consensus and containment control problems of second-order heterogeneous nonlinear MASs with full states available is proposed based on a nonsingular sliding-mode control method constructed by designing a prescribed-time convergent sliding surface. For the scenario of immeasurable velocity, a fixed-time convergent states' observer is designed to reveal the velocity information when the unknown linearity is bounded. Subsequently, a distributed fixed-time consensus protocol based on observed velocity information is proposed for the extended results. Ultimately, the acquired results are verified by three simulation examples.

Simplified ADP-Based Distributed Event-Triggered Fault-Tolerant Control of Heterogeneous Nonlinear Multiagent Systems With Full-State Constraints

Simplified ADP-Based Distributed Event-Triggered Fault-Tolerant Control of Heterogeneous Nonlinear Multiagent Systems With Full-State Constraints

Event-triggered distributed cross-dimensional formation control for heterogeneous multi-agent systems

Event-triggered distributed cross-dimensional formation control for heterogeneous multi-agent systems

Controllability of heterogeneous multi-agent systems via cooperative output regulation

This paper investigates the controllability of heterogeneous linear multi-agent systems (MASs) based on the cooperative output regulation, in which the considered agents are of high-degree heterogeneity, including different dimensions, heterogeneous dynamics and nonidentical interactions varying with agent and its neighbors. A design framework is developed for nonidentical external input and interaction gains, with the help of the improved cooperative regulators and virtual triple. Some necessary and/or sufficient conditions are derived to ensure the controllability of MASs. The obtained controllability criteria require lower computational cost and are much easier to examine compared with directly performing the traditional controllability test on heterogeneous MASs. Furthermore, extended controllability analysis without regulation assumptions is also provided to illustrate the effect of interactions among diverse agents on the controllability. The effectiveness of theoretical results is substantiated finally by two examples: a 6-agents heterogeneous MAS and a practical MAS composed of heterogeneous aircrafts and vehicles.

Leader-Following Secure Output Consensus of Heterogeneous Multiagent Systems Based on Two Sampling Mechanisms Under Hybrid Cyber-Attacks.

This article investigates the leader-following secure output consensus (LFSOC) problem of the heterogeneous multiagent systems (MASs) under the hybrid cyber-attacks. A novel hybrid cyber-attack model consisting of aperiodic additive deception (AAD) attacks and aperiodic denial of service (ADoS) attacks is proposed for characterizing cyber-attacks in a real network, where the aperiodicity is reflected in the fact that the duration of each cyber-attack can be different. First, a compensator is introduced for each agent to estimate the leader's state. Second, two sampling mechanisms consisting of a multirate sampling (MRS) mechanism and a periodic sampling mechanism are employed for heterogeneous MASs. The MRS mechanism is used to obtain real-time sampled data on the different physical variables of each agent. The periodic sampling mechanism is applied to sample the agents' compensators and the sampled data are broadcast to their neighbors immediately through a network. By selecting an appropriate sampling period (i.e., a communication period of the compensators), the robustness of heterogeneous MASs against hybrid cyber-attacks can be enhanced. Then, the appropriate communication period is selected for the compensators in different network environments by taking into consideration the cyber-attack parameters. Under these two sampling mechanisms, a sync controller is developed to achieve the LFSOC of heterogeneous MASs. Finally, an example is presented to verify the effectiveness of the proposed approach.

Output-Feedback-Based Adaptive Leaderless Consensus for Heterogenous Nonlinear Multiagent Systems With Switching Topologies.

This article investigates the leaderless output consensus control problem for a class of nonlinear multiagent systems with heterogenous system orders and unmatched unknown parameters via output-feedback control. The interaction topology among the agents is undirected and jointly connected. Due to the heterogenous system orders and switching topology among the agents, the classical distributed adaptive backstepping-based control technique cannot be applied to solve the problem considered in this article. To solve this issue, a novel distributed reference system is first proposed for each agent, by using only relative outputs of the neighboring agents. Subsequently, a fully distributed reference system-based adaptive leaderless output consensus control scheme is designed via output-feedback control. A remarkable merit of the proposed control scheme lies in that precisely known nonlinear dynamics, system states, distributed parameter estimates, and the states of virtual reference system are no longer needed to be shared with neighbors. This implies that the communication burden can be effectively alleviated, and even the communication network can be replaced by some perception sensors. Finally, two illustrative examples are provided to verify the effectiveness of the proposed control scheme.

Observer-based bipartite output containment control of heterogeneous multi-agent systems over structurally unbalanced signed graphs

In this paper, we propose state feedback and output feedback observer-based protocols that solve the bipartite output containment (BOC) problem for heterogeneous multi-agent systems over structurally unbalanced signed graphs. The proposed protocols rely solely on the exchange of output information among neighboring agents, resulting in a significant reduction or complete elimination of communication costs. Two design methods for determining controller parameters based on algebraic Riccati equations and linear matrix inequalities (LMIs) are proposed. Each method offers distinct advantages while ensuring that the closed-loop system poles are placed within a predefined region in the complex plane. Furthermore, an extensive solvability analysis is conducted, demonstrating that the solvability of the BOC problem using the proposed approach can be pre-guaranteed for a broad range of agent dynamics.

Research on fixed-time time-varying formation of heterogeneous multi-agent systems based on tracking error observer under DoS attacks

In this paper, the fixed-time time-varying formation of heterogeneous multi-agent systems (MASs) based on tracking error observer under denial-of-service (DoS) attacks is investigated. Firstly, the dynamic pinning strategy is used to reconstruct the communication channel for the system that suffers from DoS attacks to prevent the discontinuous transmission information of the communication network from affecting MASs formation. Then, considering that the leader state is not available to each follower under DoS attacks, a fixed-time distributed observer without velocity information is constructed to estimate the tracking error between followers and the leader. Finally, adaptive radial basis function neural network (RBFNN) is used to approximate the unknown ensemble disturbances in the system, and the fixed-time time-varying formation scheme is designed with the constructed observer. The effectiveness of the proposed control algorithm is demonstrated by the numerical simulation.

Model-free adaptive bipartite consensus control for unknown heterogeneous nonlinear MASs with different input delays

In this paper, a novel model-free adaptive bipartite consensus control scheme is proposed for unknown heterogeneous nonlinear multi-agent systems (MASs) with different input delays. Firstly, an equivalent data model is established for each agent by using the dynamic linearisation method. Secondly, based on an established equivalent data model and constructed predictive compensation algorithm, the distributed model-free adaptive bipartite consensus control scheme (DMFABCC) is designed by only utilising the measured input/output data rather than the state-space model of MASs. Next, by selecting an appropriate Lyapunov function, the convergence of bipartite tracking error is rigorously proved. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed DMFABCC scheme for achieving the bipartite consensus target.

Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach

This paper studies the containment control problem of heterogeneous multi-agent systems (MASs) with multiple leaders. The follower agent dynamics are assumed to be unknown and nonlinear. First, each follower is transformed into an incremental data description based on the dynamic linearization technique. Then, a distributed model-free adaptive containment control law is proposed such that all followers will be driven into the convex hull of the leaders. Furthermore, the algorithm is extended to the time-switching and dynamic leaders case. As a data-driven approach, the proposed controller design uses only the received input and output (I/O) data of these agents rather than agent mathematical models. Finally, to test the potential in real applications, three representative examples considering various environment factors, including external disturbances, are simulated to show the effectiveness and resilience of this method.

Adaptive fault-tolerant control for a class of nonlinear multi-agent systems with multiple unknown time-varying control directions

In this paper, we investigate the consensus tracking control for a class of heterogeneous multi-agent systems with multiple unknown time-varying control directions and unknown direction actuator faults. Different from existing work, the directions of the multiple time-varying control coefficients are subject to fault-induced sign-switching. To address this challenge, a series of high-order Lyapunov functions and differentiable functions are introduced to avoid non-integrable terms. Then, a novel contradiction statement and some Nussbaum functions are used to handle the summation of multiple unknown control coefficients with time-varying amplitudes and directions. Meanwhile, a novel distributed observer with quantized communication is introduced to track a reference trajectory with unknown dynamics. It is shown that all closed-loop signals are globally uniformly bounded and the tracking errors converge to residual sets that can be made arbitrarily small. Simulation results illustrate the effectiveness of the proposed scheme.

Adaptive neural event-triggered consensus control for unknown nonlinear second-order delayed multi-agent systems

In this paper, we discuss event-triggered consensus control for a heterogeneous second-order multi-agent systems with unknown nonlinear functions and state delays (SODMASs). Firstly, a broad adaptive dynamic event-triggered mechanism (ETM), which includes many existing ETM, is proposed. Based on this ETM and the approximation property of neural networks, an adaptive event-triggered protocol with weight estimation of neural network and time-varying integral gain compensation is designed to reduce communication frequency and to eliminate the uncertainty of nonlinear function and state delays. Then, the consensus problem for the heterogeneous SODMASs under the protocol is solved successfully by selecting a suitable Lyapunov–Krasovskii functional. In addition to these, it is also proved that all agents can exclude Zeno behavior under the proposed event-triggered protocol. Finally, a numerical example is given to verify the effectiveness of the proposed consensus protocol algorithm.

Adaptive containment control for heterogeneous MASs with unknown leaders and actuator failures

This paper investigates the containment control problem for heterogeneous multi-agent systems with unknown leaders and actuator failures. The dynamics of the leaders are unavailable to all followers and the measurable information of leaders is available to some followers. A model-free adaptive observer for each follower is proposed to estimate the convex hull of the leaders states and the dynamic knowledge of the unknown leaders. The followers may be affected by the actuator failures. Based on the adaptive observer and the adaptive solution of the output regulation equation, an adaptive fault-tolerant control protocol is designed to mitigate the impact of actuator failure on containment performance such that the output containment errors are ultimately uniformly bounded. Two simulation examples are provided to demonstrate the feasibility of the presented control scheme.

Secure output consensus for multi-agent systems under edge-based event-trigger against denial-of-service

This paper is concerned with the secure output consensus problem for the heterogeneous multi-agent systems under the event-triggered scheme in the presence of the denial-of-service attack. Without detecting the attack, the hold-input controller update strategy is adopted when some transmission data may be lost due to the effect of the attack. Based on the tolerable duration of the attack, a novel edge-based event-triggered scheme is developed. The scheme can avoid continuous communication and exclude Zeno behavior. With the aid of the switched system theory, output consensus is preserved. An example shows the effectiveness.

Fuzzy Adaptive Containment Control for Fractional-Order Heterogeneous Multi-agent Systems with Distributed Time-Varying Delays and Input Saturation

Fuzzy Adaptive Containment Control for Fractional-Order Heterogeneous Multi-agent Systems with Distributed Time-Varying Delays and Input Saturation

Event-Triggered Adaptive Containment Control for Heterogeneous Stochastic Nonlinear Multiagent Systems.

This article investigates the event-triggered adaptive containment control problem for a class of stochastic nonlinear multiagent systems with unmeasurable states. A stochastic system with unknown heterogeneous dynamics is established to describe the agents in a random vibration environment. Besides, the uncertain nonlinear dynamics are approximated by radial basis function neural networks (NNs), and the unmeasured states are estimated by constructing the NN-based observer. In addition, the switching-threshold-based event-triggered control method is adopted with the hope of reducing communication consumption and balancing system performance and network constraints. Moreover, we develop the novel distributed containment controller by utilizing the adaptive backstepping control strategy and the dynamic surface control (DSC) approach such that the output of each follower converges to the convex hull spanned by multiple leaders, and all signals of the closed-loop system are cooperatively semi-globally uniformly ultimately bounded in mean square. Finally, we verify the efficiency of the proposed controller by the simulation examples.

Output Consensus of Heterogeneous Multiagent Systems With Mismatched Uncertainties and Measurement Noises: An ADRC Approach

Output Consensus of Heterogeneous Multiagent Systems With Mismatched Uncertainties and Measurement Noises: An ADRC Approach

Containment control of heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded delays

This paper addresses the problem of containment control for heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded communication delays. The objective is to design a distributed control strategy that ensures the output of each follower converges to the convex hull formed by the outputs of a group of leaders in mean square sense. A novel distributed observer is proposed by tackling both Markovian randomly switching topologies and unbounded delays. Then, a distributed state feedback controller and a distributed output feedback controller are developed based on the distributed observer, respectively. Finally, simulation results are provided to demonstrate the effectiveness of the proposed controllers.

Distributed Fault-Tolerant Control for Nonlinear Heterogeneous Multiagent System With Fault Indication Under Safety Constraint

Distributed Fault-Tolerant Control for Nonlinear Heterogeneous Multiagent System With Fault Indication Under Safety Constraint

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems