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For multi-agent systems, significantly adding to the complexity of dynamical behaviors are intrinsic nonlinearity and stochastic noises due to environmental uncertainties. This paper deals with the mean square bounded consensus problem of multi-agent systems with intrinsic nonlinear dynamics, where each agent is affected by stochastic noises. Considering the impact of the former behaviors of nonlinear agents, we put forward a novel type of integral distributed delay protocol which is formed as a weighted sum of historical information exchange over all time interval [ t − τ , t ] . Compared with the previous work, the protocol expression of this paper is more general and includes many traditional protocols as its special cases. Based on a Lyapunov-based approach, together with results from matrix theory and algebraic graph theory, sufficient conditions are derived for the mean square bounded consensus. Simulation examples with nonlinear even chaotic agents illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

The cooperative exponential synchronization of multi-agent chaotic delayed neural networks (DNNs) with switching topology, stochastic disturbance and impulsive disturbance is investigated in this paper. Based on the Lyapunov stability theory, algebraic graph theory, matrix theory and the helpful stochastic Halanay inequality technique, some sufficient conditions are presented to guarantee the cooperative exponential synchronization for multi-agent chaotic DNNs with switching topology. Compared with the existing works about synchronization (or consensus) of multi-agent systems, the proposed method in this paper can provide a more general framework for the cooperative synchronization of nonlinear multi-agent systems with or without time delays, stochastic and impulsive disturbances. The famous master–slave (drive-response) synchronization of chaotic DNNs is a special case of this paper, and therefore the derived results can also be favorable for practical application in secure communication. Simulation results finally verify the effectiveness of the proposed synchronization control algorithm. [ABSTRACT FROM AUTHOR]

In this paper an agent-based social contagion model with an underlying dynamic network is proposed and analyzed. In contrast to the existing social contagion models, the strength of links between agents changes gradually rather than abruptly based on a threshold mechanism. An essential feature of the model – the ability to form clusters – is extensively investigated in the paper analytically and by simulation. Specifically, the distribution of clusters in random and scale-free networks is investigated, the dynamics of links within and between clusters are determined, the minimal distance between two clusters is identified. Moreover, model abstraction methods are proposed by using which aggregated opinion states of clusters of agents can be approximated with a high accuracy. These techniques also improve the computational efficiency of social contagion models (up to 6 times). [ABSTRACT FROM AUTHOR]

In this paper strategies for the A-Team with Reinforcement Learning (RL) for solving the Resource Constrained Project Scheduling Problem (RCPSP) are proposed and experimentally validated. The RCPSP belongs to the NP-hard problem class. To solve this problem a team of asynchronous agents (A-Team) has been implemented using the JABAT multiagent system. An A-Team is the set of objects including multiple agents and the common memory which through interactions produce solutions of optimization problems. These interactions are usually managed by a static strategy. In this paper the dynamic learning strategies are suggested. The proposed strategies based on reinforcement learning supervising interactions between optimization agents and the common memory. To validate the approach and compare strategies computational experiment has been carried out. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the distributed resource constrained multi-project scheduling problem (DRCMPSP) and focus on handling resource conflicts. The resource conflicts among projects are originally caused by precedence constraints and resource constraints. To reflect the influences of both constraints, this paper incorporates the critical chain concept into the distributed problem and introduces a corresponding heuristic strategy. Besides, to deal with large scale instances, an elimination mechanism is proposed, which identifies a few conflict time slots in advance and allocates global resources in those time slots only. Depending upon the heuristics and elimination mechanism, we develop a distributed multi-agent system based algorithm called DMAS/EM. Experiments show that DMAS/EM algorithm can generate satisfactory solutions with low average project delay and significant time savings. Furthermore, we observe that our algorithm provides great scalability with respect to variations in the size of instances processed and the degree of conflicts. [ABSTRACT FROM AUTHOR]

In order to bring the theoretical results into harmony or agreement with the reality, this paper copes with the leader-following mean square consensus issue for a class of nonlinear stochastic multi-agent systems with randomly occurring nonlinearities (RONs) and randomly occurring uncertainties (ROUs) under impulse time windows (ITWs). As a majorizing preconfigured mechanism of the windows, the configuration named periodically variable impulse time windows (PVITWs) is put forward. It not only ensures the periodic-based layout of impulse time window (ITW), but also allows the position and width of the window to be arbitrarily adjustable, so that the preset of ITW is more suitable for applications. Based on the Lyapunov stability theory and graph theory, the corresponding sufficient mean square consensus criteria are given. Finally, the feasibility of theoretical analysis is illustrated by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper addresses multi-group formation tracking (MGFT) control problems for second-order nonlinear multi-agent systems (MASs) with multiple leaders via distributed impulsive control methods. The objective is to design formation tracking protocols such that agents divide into multiple subgroups with following different leaders while maintaining desired sub-formation configurations. Distributed impulsive control protocols are proposed for MGFT control of second-order nonlinear MASs without and with the input delay. In these protocols, information exchanges among agents are only transmitted at impulsive instants. Based on the Lyapunov stability theory, some sufficient conditions are established to ensure that MASs are globally exponentially stable with and without the input delay, respectively. Examples are given to show the effectiveness of our theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies the cooperative attack tolerant tracking control problem for multi-agent systems under sensor attacks. A group of distributed adaptive state observers with a resilient switching scheme is proposed to reconstruct the states, then the tracking control strategy is designed based on the estimates. It is shown that both of the estimation and the attack tolerance control performances are ensured despite of multiple sensor attacks and the disturbances. Finally, the experimental results of networked multi-axis motion control show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the distributed leader-following consensus control problems of position-constrained multiple Euler-Lagrange Systems (ELSs) with unknown control directions. The objective of our discussion is to develop a consensus protocol despite the existence of position constraints and unknown control directions in each agent. Most of the existing works related to state constraints are for single systems and rare results are concerned about multi-agent systems. With the help of the barrier Lyapunov function, Nussbaum gain adjusting technique, and adaptive control methodology, a novel leader-following consensus algorithm is successfully designed to make sure the convergence to zero of the consensus errors and the boundedness of the signals in the closed-loop system. Moreover, the position constraints for each agent are never violated for all time during the control process. The effectiveness of the main result is illustrated by a practical mechanical system. [ABSTRACT FROM AUTHOR]

This paper investigates complete controllability and structural controllability of discrete-time multi-agent systems (MASs) under a leader-follower framework with time-delays based on absolute protocol, respectively, where both a single time-delay and multiple time-delays are investigated. By using the equivalent augmented systems without time-delays, some new graph-theoretic and algebraic characterizations are respectively built for complete controllability and structural controllability depending on communication flows of MASs. In addition, the simulation results are given. [ABSTRACT FROM AUTHOR]

This paper considers bounded consensus problem of continuous-time linear multi-agent systems with both additive system and communication noises under an undirected communication topology. Owning to the coexistence of the additive system and communication noises, the exact consensus cannot reach. Hence, the distributed controller is to be designed such that all the agents can reach to a collection behavior to some degree. It is supposed that each agent can obtain full state of itself and receive its neighbors' state with additive noises. For each agent, the consensus protocol is designed based on the error between the estimated state of its neighbors' and full state of itself. By means of Kalman filtering and matrix analysis, the bound of consensus is given via the solution of a Lyapunov equation. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In this contribution, we aim to examine the scaled consensus problem for heterogeneous multi-agent systems, which comprise two kinds of agents: the agents with first-order dynamics and the agents with second-order dynamics. The scaled consensus here means that the ratios between the states of the agents asymptotically approach specified constants instead of the same value. Firstly, appropriate distributed control protocols are designed for first-order and second-order networked agents, respectively. Particularly, the effects of switching communication networks and time-varying delays on model performance are investigated in this paper. Secondly, an augmented system approach based on algebraic graph theory and non-negative matrix theory is adopted to solve the proposed scaled consensus problem. Finally, a sufficient criterion is established to certify the scaled consensus performance of mixed agents. The correctness of the theoretical result is demonstrated through several simulation examples. [ABSTRACT FROM AUTHOR]

This paper addresses the bipartite output consensus problem of heterogeneous multi-agent systems, where the agents have different dynamics. Under the assumption that the communication topology has a spanning tree and the information of the leader is accessible only to a fraction of followers, an adaptive distributed bipartite observer is designed for every follower to estimate some information of the leader. By combining the output regulator equation and reduced-order observer design, an output feedback control law is proposed for solving the bipartite output consensus problem. At last, a simulation example is provided to show the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem of multi-agent systems (MASs) with false data injection (FDI) attacks and noises. Based on the graphical method and Kalman filter framework, distributed state estimators are designed for the agents to estimate the states of neighbors. A threshold comparison approach is proposed to obtain the secure states. Combining the state estimation approach with the threshold scheme, security mechanism is put forward to ensure the mean square consensus of MASs subject to FDI attacks. Finally, numerical simulations are provided to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

This paper considers the online optimal consensus control problem for unknown linear discrete-time (DT) multi-agent systems (MASs). Based on time-based adaptive dynamic programming (ADP) method, the control policies are designed by utilizing the current and recorded data of unknown MASs. The critic-actor NN frameworks are employed to approximate the performance indexes and optimal control policies, respectively. The NN weights are updated once at the sampling instant to produce real-time online control. Furthermore, the control policies are proved to effectively drive the MASs to achieve consistency and satisfy the Nash equilibrium. Finally, a numerical example is implemented to shown the feasibility of the control scheme. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of group consensus for a novel network model, which possesses a two-layer structure and consists of multiple interactive agents. Agents in the network are divided into several different groups according to hybrid interactions, then two neighboring agents can belong to the same group, different groups but in the same layer or different layers. Correspondingly, three kinds of relationships exist between neighboring agents in the network. Furthermore, consider that only agents in the first layer are pinned by virtual leaders, then based on the graph theory, Lyapunov function method, and optimization technique, some criteria for realizing group consensus of the network under fixed topology and switching topologies are established, which mainly depend on the topology and time intervals of the switching signal. It is found out that when the group consensus is achieved, the agents in the first layer follow the leaders asymptotically, while the agents in the second layer converge to opposite states of the leaders. Finally, a detailed numerical example is given for illustration. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of finite-time consensus tracking control for a class of 2-order nonlinear multi-agent systems (MASs). In order to present a consensus control protocol by adaptive neural control approach, a novel fast finite-time stability criterion is first set up, which provides a theoretical basis for applying approximation-based adaptive control approaches to solve the finite-time control issues. Furthermore, an adaptive neural fast finite-time consensus tracking controller is constructed based on the developed finite-time stability criterion. The suggested adaptive neural backstepping control design scheme successfully avoids the problem of singularity of controllers. Under the action of the presented protocol, the output of each follower tracks the reference signal and other signals of the closed-loop system remain bounded in finite time. The efficacy of the proposed control scheme is confirmed by simulation study. [ABSTRACT FROM AUTHOR]

This paper investigates consensus of linear multi-agent systems (MASs) with exogenous disturbances and intermittent communication. Based on a disturbance-observer method, both distributed state feedback and output feedback intermittent consensus protocols are proposed by using estimated disturbance and local relative information. And the consensus conditions are obtained by using Lyapunov stability theory. Finally, two numerical simulation examples are given to illustrate the proposed theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, semi-global leader-following output consensus problem for heterogeneous fractional-order multi-agent systems with input saturation and external disturbances is investigated. The case where the dynamics are integer-order can be viewed as a special case of fractional-order systems. First, a novel observer-based consensus algorithm is designed to solve the semi-global output consensus problem. It is worth noting that the consensus is semi-global since the set of initial states is bounded. Then, the low gain feedback technique is utilized based on the solution of a parametric algebraic Riccati equation. Moreover, sufficient conditions of output consensus for heterogeneous fractional-order multi-agent systems are derived by using algebraic graph theory, matrix theory and the stability theory of fractional-order systems. It can be proven that the output signals of followers can reach synchronization with the leader's. Finally, numerical examples are provided to illustrate the effectiveness of our conclusions. [ABSTRACT FROM AUTHOR]

In this paper, the problem of reachable set estimation of multi-agent systems (MASs) is investigated. For the ease of application, balanced communication topology with a directed spanning tree and non-zero initial condition are considered. Based on the Lyapunov method and orthogonal transformation technique, sufficient conditions are established in terms of linear matrix inequalities to guarantee that the reachable set of MASs is bounded by a compact ellipsoid. Moreover, by employing some useful skills from stochastic analysis, the result is then extended to the problem for MASs under Markovian switching topologies. The effectiveness of the obtained results is illustrated by two numerical examples. [ABSTRACT FROM AUTHOR]

The paper addresses a distributed containment issue for a stochastic nonlinear strict-feedback multi-agent system. In combination with the graph theory and neural networks technique, an adaptive neural containment protocol is developed within the traditional backstepping framework. Such a containment protocol allows one to extend some existing results to the case that multiple followers are confined to stochastic nonlinear dynamics. Furthermore, with the help of the quartic Lyapunov function, it is proved that all the signals in the resulting closed-loop system remain bounded in probability and the containment error converges to a small neighborhood of the origin in the sense of mean square by a suitable choice of parameters. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed protocol. [ABSTRACT FROM AUTHOR]

This paper is concerned with distributed event-triggered consensus of a generally linear multi-agent system subjected to periodic denial-of-service (DoS) jamming attacks. First, a novel switched time-varying delay system model is established to describe consensus error dynamics. By virtue of the switched system and time delay system approaches, one constraint is obtained as a tradeoff between exponential convergence rate of consensus error and uniform lower bound of sleep intervals of periodic DoS jamming attacks. Second, sufficient conditions are derived to guarantee exponential consensus of the multi-agent system. Third, a co-design method is presented to determine the parameters of both the distributed event-triggered mechanism and consensus protocol. Furthermore, an algorithm is given to find the allowable uniform lower bound of sleep intervals and suboptimal distributed event-triggering parameters. Finally, an illustrative example is provided to verify the effectiveness of the proposed resilient event-triggering consensus design method against periodic DoS jamming attacks. [ABSTRACT FROM AUTHOR]

This paper investigates the consensus problem of multi-agent systems with intermittent communications under sampled-data control. A novel approach called sampling time unit (STU) approach is proposed to study such system. In such approach, the work time is described by finite number of sampling time units and the rest time is describe by several average time units. The lengths of work time and rest time depend on the convergence or divergence property of each time unit. Based on the STU approach, the stabilization property at transition instants can be derived, which can compensate the divergence during rest time to some extents. The designed control scheme can tolerate a relatively large rest time. Based on the STU approach, a corresponding sampling-dependent time-varying Lyapunov function (SDTVLF) is utilized to describe the system state and derive the computable conditions for the overall consensus with maximum admissible rest time. Finally, a numerical example with two cases is provided to illustrate the feasibility of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper concentrates on the adaptive neural finite-time bipartite consensus tracking of nonstrict feedback nonlinear coopetition multi-agent systems with input saturation. A novel consensus tracking method combined the adaptive neural control with the finite-time command filtered backstepping is proposed. During each backstepping process, the Radical Basis Function Neural Network (RBF NN) is used to approximate the unknown nonlinear dynamics and the finite-time sliding mode differentiator (FTSMD) is used to obtain intermediate signals and their derivative. Moreover, the filtering errors are eliminated by using error compensation signals. By using the finite-time Lyapunov stability theory, it can be proved that the bipartite consensus tracking errors can converge to a sufficient small region of the origin in finite-time and all signals in the closed-loop systems are bounded in finite-time although there exists the input saturation. The effectiveness of the proposed method is shown by simulation results. [ABSTRACT FROM AUTHOR]

In this paper, the circle formation control problem of second-order multi-agent systems which are constrained to move on a circle is considered. Each agent can only measure the positions and velocities of its neighbors with bounded measurement errors. Using these inaccurate measurements, a distributed formation control laws is developed for each mobile agent. It is shown that under the proposed control law the multi-agent system can be driven to a neighborhood of the desired circle formation. The upper bound on the agents' formation errors in the final configuration is also provided. Note that collision between mobile agents can be prevented if the agents' spatial order on the circle is always preserved. The conditions under which order preservation of the agents is guaranteed during the formation task are also given. Finally, a simulation example is provided to illustrate the effectiveness of the proposed formation control law. [ABSTRACT FROM AUTHOR]

In this paper, formation control problem for multiple uncertain nonlinear second-order agents in the presence of heterogeneous communication delays is addressed. A continuous repulsive vector is incorporated into agents' velocity to ensure collision avoidance, whose time derivative is approximated via a finite-time robust integral of the sign of the error (RISE)-like observer. Using adaptive neural control scheme, unknown model dynamics, external disturbances, RISE estimation error, and the time-delays among agents are robustly addressed. The sufficient conditions on the stability of the overall system and collision avoidance are derived using Lyapunov–Krasovskii functionals and algebraic graph theory, and it is proven that the formation tracking error converges to a small neighborhood of zero. Numerical simulation results are also given to illustrate the effectiveness of our proposed methods. [ABSTRACT FROM AUTHOR]

This paper mainly tends to address distributed bipartite tracking consensus problem for nonlinear multi-agent systems subject to logarithmic quantization. Based on appropriate quantized criterion, a distributed protocol with static coupling gain is developed. By employing Lyapunov technique and other mathematical analysis, the results show that distributed bipartite tracking consensus of multi-agent systems can be ensured with quantized relative state measurements, if some conditions are met. Additionally, compared with distributed protocol, the fully distributed protocol with dynamic coupling gain is further designed and analyzed via adaptive control, which is independent of any global information. Finally, simulations are exploited to support our theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper studies the containment control problem for high-order continuous-time multi-agent systems (MASs) under switching topologies and time-varying delays. We propose a distributed sampled-time containment protocol in which the restriction of choosing weights of the communication links from a finite set is eliminated. Under such a protocol, the states of the followers will asymptotically converge to the convex hull spanned by those of the leaders. Based on the properties of scrambling matrices, necessary and sufficient containment criteria are obtained for the network of agents with arbitrary bounded communication delays and switching interaction topologies. The proposed condition does not need the communication graph has a united spanning tree at each time instant and only requires that the union of communication graphs has a united spanning tree over a bounded period of time. In addition, the appropriate feedback gains are computed via given mathematical relations. Some numerical examples are given to demonstrate the effectiveness of the new protocols. [ABSTRACT FROM AUTHOR]

This paper presents the event-triggered consensus control problem for a class of multi-agent systems (MASs) in the non-affine form. An error-transformation-based design method is presented in the non-affine MASs. The radial basis function neural networks (RBFNNs) are used to approximate the unknown nonlinear functions. The dynamic surface control (DSC) technique is adopted to obtain parameters of the virtual controller through a first-order filter, which can make the calculation easier. An event-triggered control strategy is proposed to reduce communication frequency. Furthermore, it is further shown that the consensus tracking errors are semi-globally uniformly ultimately bounded (SGUUB). Finally, simulation results illustrate the effectiveness of the designed controller. [ABSTRACT FROM AUTHOR]

We respond to the consensus control algorithms for second-order non-linear MAS with unknown control gains in the finite time interval by adopting iterative learning control (ILC) methods in this paper. Compared to the current findings, the control gains in the proposed method are unknown functions with unknown and non-identical signs. The topology graph between the follower agents is an undirected connected graph. By referencing the Nussbaum-type function and the neural networks, the adaptive control algorithms are intended to cope with the consensus control between the agents on the limited time interval. Simulation results illustrate the efficacy of the raised algorithms. [ABSTRACT FROM AUTHOR]

The problem of group consensus is considered for a class of discrete-time heterogeneous multi-agent systems(HMASs) with time delays in this paper. Due to network-induced time delays, the predictive scheme is proposed to compensate delays actively by using the received agents' outdate information, and a novel distributed protocol with prediction of states is designed. By getting rid of a conservation condition of in-degree balance which widely exists in relevant results, necessary and/or sufficient conditions are established for group consensus control of discrete-time HMASs. Finally, simulations are demonstrated that, under the proposed theoretical results, the performance of discrete-time HMASs with time delays is similar to that without delays. [ABSTRACT FROM AUTHOR]

This paper considers the finite-time containment control problem for nonstrict-feedback nonlinear multi-agent systems (MASs) in the presence of unmodeled dynamics. A new variable separation approach is developed to overcome the difficulty of unknown functions with nonstrict-feedback structure in the backstepping design process. The second-order tracking differentiator is extended to the nonstrict-feedback nonlinear MASs for avoiding the problem of "explosion of complexity". Neural networks are used to approximate the unknown nonlinear functions. With introducing a dynamic signal, the difficulty from the unmodeled dynamics is successfully solved. And, by introducing a finite-time stability criterion, an new adaptive finite-time containment control scheme is designed, which ensures all signals are bounded. Moreover, the output signals of all followers converge to a convex hull spanned by the outputs of the leaders. Finally, a simulation example illustrates the effectiveness of the developed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, group consensus of multi-agent systems with cooperative-competitive interaction and communication delay is investigated in switching topologies networks. The delta operator method and linear matrix inequality technique are used to establish the criteria on group consensus of this system. Combined with the stability theory, some sufficient conditions are given to guard the success of the group consensus of the multi-agent systems with switching topologies. Using this method, the problem of group consensus can be transformed into determining the globally asymptotically stable of a system with communication delay. The results can be applied to two situations on faults and communication delay without meeting the in-degree balance condition or spanning tree of part topologies. Several numeric simulations are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper deals with the event-triggered leader-follower consensus problem of linear multi-agent systems with disturbances over the directed graph. By using relative output information of the neighboring agents, we develop a novel class of distributed extended state observers. With the estimated values of tracking error and coupled states of the leader's input and disturbances, event-triggered protocols are designed to solve the leader-follower consensus problem. The proposed protocols update intermittently and can suppress disturbances actively. Subsequently, we prove the systems don't exhibit Zeno behavior. Furthermore, both the input of leader and disturbances are considered as unmodeled and not available to any follower. Finally, a simulation example is provided to demonstrate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, guaranteed-performance consensus (GPC) for descriptor nonlinear multi-agent systems (DNMASs) with a leader is studied. The interactions among followers are bidirectional for leader-following DNMASs. Firstly, one designs a novel distributed nonlinear consensus protocol based on state feedback to reach consensus for DNMASs. The performance function is constructed by state errors among agents, which is time integration of quadratic function. Secondly, not only are sufficient conditions presented for guaranteed-performance consensus to ensure the scalability of DNMASs based on the Riccati inequality, but also an upper bound of the cost function is derived. It is shown that the guaranteed-performance costs are dependent on initial states of agents. Moreover, the conclusions are extended to achieve the leaderless GPC. Finally, simulation examples are presented to demonstrate the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, consensusability of the discrete-time linear multi-agent systems (MASs) with multiple inputs are considered. Both the leaderless and leader-following consensus are taken into account, and the associated communication graphs can be undirected or directed. Using an appropriately designed weighted dynamic distributed protocol, it is proved that consensusability of the MASs completely hinges on consensusability of the designed distributed dynamic compensators. New consensusability conditions are derived which are inequalities associated with the maximum absolute unstable eigenvalue of the agent's dynamics (rather than the product of all absolute unstable eigenvalues in literatures) and the eigen-ratio of the communication graph. Simulation examples are given to demonstrate the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the consensus problem is investigated for a class of nonlinear multi-agent systems in lower triangular form through dynamic output feedback control. Each agent can only access to the uncertain relative output information from other agents under directed communication. The presence of unknown measurement sensitivities causes the relative output can not be used to construct the observer for each agent directly. For the sake of overcoming this difficulty, a dual-domination gain method is applied to dominate the nonlinear terms and the unknown measurement sensitivities. Then, a new dynamic output feedback consensus prtocol is presented to drive the multi-agent systems to consensus. The upper bound of the unknown measurements sensitivities is also given. At last, we provide two numerical simulation examples to verify the effectiveness of our proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we study the distributed containment control problem with multiple leaders for nonlinear multi-agent systems (MASs) with unstabilizable linearizations under the directed topology. A novel distributed control design approach is developed to simultaneously deal with the unstabilizable linearizations and nonlinear interactions among agents. The designed controller can guarantee that the followers' outputs will eventually converge to a limit point in the convex hull spanned by the leaders' outputs while all the states of the closed-loop system remain bounded. Finally, a mechanical system example is presented to illustrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, a delay tolerant containment control problem for second-order multi-agent systems (MASs) is studied. Considering the disturbance caused by the time-varying delays between agents, we utilize the delay tolerant character of MASs with multiple leaders to redesign the topology of concerned MASs and solve the containment control problem. Corresponding sufficient and necessary conditions on the communication digraph of the MAS are developed to ensure the followers converging to interior points of a convex hull formed by the leaders. Furthermore, considering the inevitable delays between the communications of agents, we present the topology design algorithm in light of the proposed conditions to solve the delay tolerant containment control problem for the second-order MAS. In this case, we focus on how to redesign the communication topology structure instead of constructing a proper distributed cooperative controller. Finally, some examples are given to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

In this paper, the bipartite consensus problem for high-order multi-agent systems (MASs) with input saturation is investigated by distributed event-triggered control and low-gain feedback technique. The underlying topological graph of the system is divided into undirected graph and directed graph. Distributed event-triggered control strategy is proposed to guarantee the semi-global bipartite consensus of MASs. The lower bound of time interval between any two consecutive triggering instants ensures that the Zeno behavior can be excluded for each agent. Finally, two simulation examples are presented to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

The containment control problem using only sampled position data for second-order multi-agent systems (MAS) is studied in this paper. We first consider the delay-free case of the containment control protocol and obtain a necessary and sufficient condition regarding the network structure and the system parameters. Then, we obtain a similar necessary and sufficient condition for the case with time delay of the containment control protocol. Finally, several numerical simulations are performed to verify the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

The paper is concerned with containment maneuvering of nonlinear multi-input multi-output (MIMO) strict-feedback multi-agent systems under the distributed directed communication. Followers are driven into a convex hull spanned by all virtual leaders guided by desired parameterized paths. Multi-agent systems are driven to achieve the desired behavior. A containment maneuvering controller is developed based on an event-triggered modular-ISS neural network control method to decouple estimation and control. Specifically, in the estimation loop, an RBF-network-based predictor module is constructed to design the adaptation law, where an RBF network is employed to identify the uncertain nonlinear dynamics. An event-triggered communication mechanism is introduced to decrease the burden of followers communication. In the control loop, a control module is constructed by using the output of predictor module and a third-order linear tracking differentiator. An event-triggered actuation mechanism is introduced to reduce the actuator burden of followers. A path update law is constructed to achieve coordination among leaders. An event-triggered communication scheme is introduced for leaders to decrease the communication burden of leaders. The input-to-state stability of the total cascade system is demonstrated by using the cascade stability theorem. Simulation results are provided to substantiate the efficacy of the proposed containment maneuvering controller for nonlinear MIMO strict-feedback multi-agent systems. [ABSTRACT FROM AUTHOR]

This paper considers an observer-based consensus problem of linear multi-agent systems with intermittent communication. An observer-based protocol with both continuous and sampled data is proposed. Consensus criteria and protocol design are obtained by matrix theory. Compared with the previous protocol, it is shown that our protocol can solve the consensus problem with lower communication time rate especially when the time interval without communication is sufficiently short. Finally, several examples are provided to show the effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem of second-order multi-agent systems by means of the event-triggered approach. A novel protocol, which relaxes the mutual requirement on the velocity measurements of nodes, is proposed under the general directed topology. The proposed law is further extended to the case of changing coupling gains, that is, the node/edge-based scheme. It suggests that the variable coupling weights merely enhance or weaken the communication capacity among the nodes, while do not essentially change the structure of sensing graph. It hence gives some insight into the balance between performance index and configuration budget. Moreover, compared with the infinite precision computation algorithm, our quantization-based triggering rule is concretely designed to explore mild consensus criteria. Finally, numerical examples are presented to support the effectiveness of the proposed cooperation rules. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of bipartite output consensus of heterogeneous linear multi-agent systems with antagonistic interactions. The signed graph is directed and structurally balanced. With the assumption that only the leader can access the output of exosystem, two fully distributed adaptive protocols without using the state information of exosystem are designed based on the states and the observers of states, respectively. Numerical simulation demonstrates the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the bipartite state synchronization problem of heterogeneous multi-agent systems (MASs) with active leader under adversarial signals over signed digraph is studied. The non-zero control of active leader is bounded, and we can update this control to protect followers from possible danger. Firstly, the bipartite state synchronization problem over signed digraph is converted to a regular tracking synchronization problem over nonnegative digraph after state transformations for heterogeneous MASs with active leader under adversarial signals. Then, novel distributed observers are designed to estimate the state of leader, as well as prevent disrupted data of agent from propagating the communication networks. Observer-based H ∞ optimal controllers are also designed for each follower to mitigate effects on disrupted agents that agents under attack, and the inhomogeneous algebraic Riccati equations (AREs) are obtained. Meanwhile, a data-based off-policy reinforcement learning (RL) algorithm is used to solve the AREs without requiring the dynamics of agents. At last, the effectiveness of the algorithm is demonstrated by a simulation example. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time consensus problem for multi-agent systems. Different from the existing results, the mismatched disturbances and actuator faults are taken into account, moreover, the communication networks are considered to be directed. By introducing fixed-time observers to estimate the faults and disturbances, a new observer-based control protocol is designed for each follower system. Under this scheme, the consensus is proved to be achieved by employing a bi-limit homogeneity technique and Lyapunov theory, and the convergence time is independent of initial conditions. Finally, simulation results are provided to verify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the bipartite finite-time output consensus problem of heterogeneous linear multi-agent systems (HL-MASs) described by a directed signed graph. First, by combining the event-triggered mechanism and finite-time control, we propose a bipartite finite-time event-triggered observer (bipartite FT-ET observer) to estimate the leader's state. Triggering condition is presented by introducing a dynamic variable. Compared with conventional observer to solve the output consensus problem, exact estimation of the leader's state can be achieved by only intermitted communication among agents. Moreover, Zeno behavior can be avoided by choosing parameters appropriately. Then, we construct a finite-time controller based on bipartite FT-ET observer, such that the bipartite output consensus can be achieved in a finite time. Finally, an example is provided to illustrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

This paper proposes optimal bipartite consensus issue for discrete-time multi-agent system (DTMAS) using event-triggered control (ETC) and quantized event-triggered control (QETC). Firstly, a novel event-triggered control strategy is introduced along with specific conditions to ensure the stability for DTMAS. Due to the intractability of the Hamilton–Jacobi–Bellman (HJB) equation, through two neural networks (NNs), the value function and optimal control are approximated by the adaptive dynamic programming (ADP) method. The weight matrix of the action neural network is updated only when triggered, while also taking into account the quantization effect of the information. The stability of the weights errors and the convergence of the system dynamic are demonstrated using Lyapunov stability theory. Finally, the practicality of the improved method is confirmed a numerical example. [ABSTRACT FROM AUTHOR]

This paper addresses the formation consensus tracking control problem of uncertain dynamical multi-agent system with nonlinear dynamics based on a leader–follower configuration based on a undirected communication topology. The control design is based on a novel combination of consensus protocols and dynamical neural networks, known as differential neural networks, to approximate the modeling uncertainties and external disturbances of the follower agents. The proposed controller-identifier structure forces the state of each agent to maintain a formation with respect to the leader ensuring limited residual errors. The stability proof supports the control design and guarantees the multi-agent system states to be ultimately bounded. In order to show the effectiveness of the proposed tracking controller and the superior performance against the static RBFNNs approach, some simulation results are presented considering a multi-robotic system with five agents following a helical three-dimensional reference signal of a virtual leader. [ABSTRACT FROM AUTHOR]