Consensus Of Nonlinear Multi-agent Systems Research Articles

Feedforward compensator based fuzzy adaptive asymptotic consensus for nonlinear multiagent systems

Feedforward compensator based fuzzy adaptive asymptotic consensus for nonlinear multiagent systems

Adaptive predefined-time consensus for nonlinear multi-agent systems with input delay and performance constraints

This paper investigates the predefined-time tracking consensus issue for a class of non strict-feedback nonlinear multi-agent systems (MASs) under input delay and error performance constraints by adaptive backstepping control strategy. Firstly, the impact of input delay is eliminated by Pade approximation. With the help of an intermediate state variable, the considered MASs with input delay are revised as the independent-delay systems. Secondly, under constrained distributed error and corrected nth virtual error, the ln-type barrier Lyapunov function (BLF) is adopted to solve the error performance constrains and reduce the complexity of differentiation. Meanwhile, an adaptive predefined-time controller is designed to realize the tracking purpose by backstepping method and radial basis function neural networks (RBFNNs) approximation. Finally, a numerical simulation example and a practical application are presented to test the effectiveness for the proposed control strategy.

A Novel Parallel Control Method for Optimal Consensus of Nonlinear Multiagent Systems.

This work concentrates on the initial introduction of parallel control to investigate an optimal consensus control strategy for continuous-time nonlinear multiagent systems (MASs) via adaptive dynamic programming (ADP). First, the control input is integrated into the feedback system for parallel control, facilitating an augmented system's optimal consensus control with an appropriate augmented performance index function to be established, which is identical to the original system's suboptimal control with a conventional performance index. Second, the feasibility of the proposed control scheme is evaluated based on the policy iteration algorithm, and the convergence of the algorithm is demonstrated. Then, an online learning algorithm becomes available to implement the ADP-based optimal parallel consensus control protocol without prior knowledge of the system. The Lyapunov approach is employed to indicate that the signals are convergent. Ultimately, the experimental data support the theoretical results.

Fully distributed practical fixed-time fault-tolerant consensus of nonlinear multiagent systems

In this article, the practical fixed-time fault-tolerant consensus problem of a class of first-order nonlinear multiagent systems with actuator faults is investigated. Owing to the existence of uncertain actuator failures (multiplicative faults and additive faults) and non-linearities, it is challenging to study the fixed-time consensus problem of such multiagent systems in a fully distributed approach. To get over this challenge, a fully distributed adaptive protocol that utilizes adaptive techniques is proposed. Under this control protocol, multiagent systems can achieve consensus, and by adjusting controller parameters, the consensus error can converge to the acceptable bounded region in a fixed time. In addition, due to the introduction of adaptive parameters, the design of the control protocol is not dependent on any global network topology information, which means the control protocol is fully distributed. Therefore, the proposed scheme has better scalability and wider applicability. Finally, the simulation results are proposed to validate the fault-tolerant ability and fully distributed characteristics of the presented scheme.

Leader-follower consensus for nonlinear multi-agent systems under directed topology

This paper investigates the consensus problem for multi-agent systems (MASs) under directed topology. The primary objective is to design the distributed control protocol such that all agents can converge to the state of leader. The distributed control protocol is designed, and we derive sufficient conditions by using Lyapunov stability theory to achieve consensus. Theoretical analysis and numerical simulations are provided to verify the effectiveness of the proposed control protocol.

Aperiodically Intermittent Event-Triggered Optimal Average Consensus for Nonlinear Multi-Agent Systems.

This article is concerned with average consensus of multi-agent systems via intermittent event-triggered strategy. First, a novel intermittent event-triggered condition is designed and the corresponding piecewise differential inequality for the condition is established. Using the established inequality, several criteria on average consensus are obtained. Second, the optimality has been investigated based on average consensus. The optimal intermittent event-triggered strategy in the sense of Nash equilibrium and corresponding local Hamilton-Jacobi-Bellman equation are derived. Third, the adaptive dynamic programming algorithm for the optimal strategy and its neural network implementation with actor-critic architecture are also given. Finally, two numerical examples are presented to show the feasibility and effectiveness of our strategies.

Distributed Dynamic Event-Triggered Leader-Following Consensus for Nonlinear Multiagent Systems Over Fading Channel.

This article investigates the leader-following consensus problem of discrete-time nonlinear multiagent systems (MASs) over fading channels. With the consideration of the transmission among followers maybe affected by the fading networks, the nonidentical fading channels model is constructed. To reduce the transmission network burden, the dynamical event-triggered mechanism (DETM) is developed. Different from most of existing event-triggered strategies, the threshold parameter in the developed dynamical event-triggering condition is dynamically adjusted according to a dynamic rule. Based on the DETM, a distributed consensus control protocol is designed under fading channels. Then, sufficient criteria are provided to ensure that MASs can achieve the leaser-following consensus, and satisfy the H∞ performance index in the presence of fading channels. The desired controller parameters can be derived in terms of solutions of matrix inequalities that are lightly solvable. In the end, simulation results show that the designed dynamical event transmission policy is capable of diminishing communication burden more promptly and effectively than some existing ones.

Switching adaptive dynamic event-triggered consensus of nonlinear multi-agent systems under DoS attacks and communication delay

This article addresses the issue of achieving security consensus in multi-agent systems (MASs) that are susceptible to denial-of-service attacks (DoS-As) and time-varying communication delays (TCD). We have developed a novel unified model to describe DoS-As and TCD. Firstly, a new switching adaptive dynamic event-triggered mechanism (SADETM) is proposed to conserve communication resources during DoS-As and TCD. The mechanism transforms into three event-triggered strategies adapted to highly dynamic MASs. Then, a consensus control protocol is designed through consensus errors based on SADETM. Finally, the sufficient conditions for ensuring the stability of MASs are solved by combining the Lyapunov-Krasovskii functional (LKF) method and the linear matrix inequality (LMI) technique. The effectiveness of this method is verified through simulation examples.

Fault-tolerant consensus of nonlinear multi-agent systems with channel noises under multiple faults and denial-of-service attacks

Fault-tolerant consensus of nonlinear multi-agent systems with channel noises under multiple faults and denial-of-service attacks

Adaptive sliding mode consensus tracking for nonlinear leader-following multi-agent systems with distributed estimation strategy

This paper studies the consensus of nonlinear multi-agent system based on distributed estimation and adaptive sliding mode control schemes. A strategy for distributed estimation is proposed to ensure that every follower is able to estimate the state of the leader within a finite time. Then a structurally simpler integral sliding manifold is designed to eliminate the reaching phase. Furthermore, two control protocols are formulated to ensure the reachability of sliding surface according to the estimated state of the leader. The first protocol is a discontinuous one that ensures exponential convergence of the consensus tracking error to zero, but its switching gain is difficult to be adjusted. Then an adaptive protocol is developed to adjust the switching gain automatically, which is the second control protocol. This protocol not only avoids chattering but also relaxes the dependence on certain boundaries. Finally, simulations are conducted to validate the efficacy of the employed strategy.

Neural-Network-Based Predefined-Time Adaptive Consensus in Nonlinear Multi-Agent Systems With Switching Topologies.

A predefined-time adaptive consensus control strategy is developed for a class of multi-agent systems containing unknown nonlinearity. The unknown dynamics and switching topologies are simultaneously considered to adapt to actual scenarios. The time required for tracking error convergence can be easily adjusted using the proposed time-varying decay functions. An efficient method is proposed to determine the expected convergence time. Subsequently, the predefined time is adjustable by regulating the parameters of the time-varying functions (TVFs). The neural network (NN) approximation technique is used to address the issue of unknown nonlinear dynamics through predefined-time consensus control. The Lyapunov stability theory testifies that the predefined-time tracking error signals are bounded and convergent. The feasibility and effectiveness of the proposed predefined-time consensus control scheme are demonstrated through the simulation results.

Data-driven leader-following consensus for nonlinear multi-agent systems against composite attacks: A twins layer approach

This paper studies the leader-following consensuses of uncertain and nonlinear multi-agent systems against composite attacks (CAs), including denial of service (DoS) attacks and actuation attacks (AAs). A double-layer control framework is formulated, where a digital twin layer (TL) is added beside the traditional cyber–physical layer (CPL), inspired by the recent Digital Twin technology. Consequently, the resilient control task against CAs can be divided into two parts: One is distributed estimation against DoS attacks on the TL, and the other is resilient decentralized tracking control against actuation attacks on the CPL. First, a distributed observer based on switching estimation law against DoS is designed on TL. Second, a distributed model-free adaptive control (DMFAC) protocol based on attack compensation against AAs is designed on CPL. Moreover, the uniformly ultimately bounded convergence of consensus error of the proposed double-layer DMFAC algorithm is strictly proved. Finally, the simulation verifies the effectiveness of the resilient double-layer control scheme.

Adaptive control for parabolic PDE based multi-agent systems

In this paper, an adaptive controller is constructed to resolve the problem of consensus for nonlinear multi-agent systems described by partial differential equations. Firstly, the nonlinear terms existed in the considered system are approximated by neural networks. Secondly, a sufficient condition on the existence of the controller for consensus is presented in terms of linear matrix inequalities. On the basis of this, the adaptive controller is designed, and the closed-loop system is proved to be stable by applying the Lyapunov stability theory. Further, the consensus is achieved for nonlinear multi-agent systems. Finally, the effectiveness of the proposed control protocol is verified by simulation examples.

PD and PI Control for the Lag Consensus of Nonlinear Multiagent Systems With and Without External Disturbances.

In this article, we investigate the lag consensus and lag H∞ consensus problems for second-order nonlinear multiagent systems (MASs) by utilizing the proportional-derivative (PD) and proportional-integral (PI) control methods. On the one hand, a criterion is developed for ensuring the lag consensus of the MAS by choosing an appropriate PD control protocol. Moreover, a PI controller is also provided to guarantee that the MAS can achieve lag consensus. On the other hand, several lag H∞ consensus criteria are also given for the case in which external disturbances appear in the MAS; these criteria are developed by exploiting the PD and PI control strategies. Finally, the devised control schemes and the developed criteria are verified by employing two numerical examples.

PI-Observer-Based Consensus of Nonlinear Multiagent Systems via Reduced-Order Edge State Dynamics and Decentralized Procedure

PI-Observer-Based Consensus of Nonlinear Multiagent Systems via Reduced-Order Edge State Dynamics and Decentralized Procedure

A Hybrid Systems Approach to Consensus of Nonlinear Multi-agent Systems With Self-triggered Output Feedback Control

A Hybrid Systems Approach to Consensus of Nonlinear Multi-agent Systems With Self-triggered Output Feedback Control

Distributed disturbance observer-based nonfragile bipartite consensus of nonlinear multiagent systems with multiple time-varying delays

The paper concentrates on the issue of distributed disturbance observer-based nonfragile bipartite consensus within nonlinear delayed multiagent systems, encompassing both leaderless and leader-following structures. The delays under consideration are nonuniform, manifesting in the state, the nonlinearity, and the communication processes. To suppress the external disturbances and the observer gain perturbations, distributed nonfragile disturbance observers pertaining to relative output and communication delays are developed to estimate the external disturbances for each agent. Employing the developed disturbance observer, distributed control protocols for nonfragile bipartite consensus are constructed incorporating states, estimated disturbances, and communication delays. These protocols can ensure bipartite consensus, compensate for external disturbances, and tolerate uncertainties in control gain. New augmented Lyapunov-Krasovskii functions are formulated by introducing the triple integral term and the augmented vector. The new bipartite consensus criteria for the studied multiagent systems are established with less conservatism by employing the techniques on second-order Bessel-Legendre integral inequality, reciprocally convex combination, and free weight matrix. Finally, numerical simulations and comparisons are performed for both leaderless and leader-following scenarios, thereby validating and enhancing the theoretical outcomes.

Adaptive impulsive consensus of nonlinear multi-agent systems via a distributed self-triggered strategy

This article investigates the consensus problem of nonlinear leader-following multi-agent systems (MASs) via adaptive impulsive control. A distributed impulsive controller is employed, in which an adaptive updating law in the discrete-time setting is designed for the impulsive gain. Moreover, in order to reduce the communication cost, a distributed self-triggered strategy is proposed to determine when the impulsive instant occurs. Some criteria are derived to guarantee consensus of leader-following MASs based on Lyapunov stability theory and algebraic Riccati equation. It is proved that the self-triggered impulsive sequence does not exhibit Zeno behaviour. Finally, an illustrative example is presented to empirically validate the effectiveness of the theoretical results.

Consensus for nonlinear multi-agent systems with actuator saturation by adaptive event-triggered scheme

This paper studies the leader–follower consensus problem for nonlinear multi-agent systems with actuator saturation by adaptive event-triggered scheme. This adaptive mechanism allows parameters in triggered mechanism to change automatically compared to fixed ones in traditional strategies. The paper introduces two distinct approaches to address the issue of saturation. The first approach is sector bounded condition, while the second relies on convex hull representation. Compared with the former one, the latter one can reduce the conservatism of controller design effectively. Furthermore, it is assumed that the nonlinear function adheres to incremental quadratic limitations, thereby offering a more comprehensive depiction of its nonlinear properties. Finally, the validity of the proposed approaches is demonstrated by one numerical example in the background of mechanical systems.

Stubborn Observer for Leader-Following Consensus of Nonlinear Multiagent Systems With Application to Spacecraft.

In this article, the leader-following consensus problem is investigated for a class of nonlinear multiagent systems with transmission outliers. First, through the relative output information and observer states of neighbor agents, a distributed stubborn reduced-order observer is proposed to estimate the leader-following consensus error which is affected by abnormal and isolated transmission outliers. Moreover, considering that the leader agent in practice is a controllable plant, another distributed stubborn reduced-order observer is designed by using the relative information and inputs of neighbor agents. Sufficient conditions are established in terms of the Laplacian matrix such that two stubborn reduced-order observers are convergent and the studied nonlinear multiagent system could achieve leader-following consensus with directed topology. Finally, an example of the multispacecraft system is provided to illustrate the effectiveness of the proposed methodology.