Scaled consensus of multi-agent systems with output saturation

This paper studies a scaled consensus problem with output saturation in the sense that the states of agents reach assigned proportions rather than a common consensus value. Specifically, we investigate single-integrator agents with output saturation under both undirected and strongly connected graphs. Some conditions for single-integrator agents with output saturation are illustrated. The main contribution is that by employing an integral Lyapunov function, a necessary and sufficient condition is first obtained to reach scaled consensus among agents with output saturation. Simulation results are presented to show the performance of the scaled consensus.     

Fixed-time scaled consensus of multi-agent systems with input delay

The design of fixed-time scaled consensus protocol for multi-agent systems with input delay is developed in this article. First, by virtue of Artstein model reduction method, the time-delay system is converted into a delay-free one. Then, two novel controllers are designed such that the fixed-time scaled consensus of multi-agent systems can be realized for the undirected and directed topology, respectively. Sufficient conditions are derived to guarantee that all agents converge to the assigned ratios instead of the same value under any bounded input delay. Besides, an explicit estimate can be given for the uniform convergence time independent of the initial conditions. Moreover, it is proved that the convergence value of the system is not affected by the initial states of agents any more, but only related to initial states of the virtual agents set in advance. Finally, numerical simulations are given to demonstrate the feasibility of the proposed algorithms.     

Scaled group consensus in agent networks with finite sub-networks under continuous/discrete-time settings

We study scaled group consensus problems of the first/second-order multi-agent dynamics under continuous/discrete-time settings. For a directed multi-agent network with finite sub-networks, the scaled group consensus is concerned with this case that all the sub-networks reach consensus, separately, while maintain the given ratios among the multiple consensus. First/second-order distributed protocols with continuous/discrete data are designed to solve the scaled group consensus problems, and then necessary and sufficient criteria are established to guarantee the agents’ states reaching the scaled group consensus asymptotically applying both algebraic and analytical tools. Finally, the effectiveness of the theoretical results are verified by several simulation examples.     

Distributed optimization with closed convex set for multi-agent networks over directed graphs

In this paper, a distributed projection algorithm based on the subgradient method is presented to solve the distributed optimization problem with a constrained set over a directed multi-agent network, where the designed protocol is scaled by the left eigenvector associated with the weighted adjacency matrix. By using the property of the projection operation and nonnegative almost supermartingales, we give the convergence analysis of our algorithm and show that the optimal solution is the ultimate consensus state of all agents to be reached. A numerical simulation for a specific optimization problem is given to verify the effectiveness of our algorithm.     

Scaled consensus problem for multi-agent systems with semi-Markov switching topologies: A view from the probability

This paper investigates the stochastic scaled consensus problem for multi-agent systems with semi-Markov switching topologies. Sufficient conditions are established to guarantee the addressed system to realize the scaled consensus with probability one, which means that all agents’ states almost surely reach a dictated proportion. Here, the semi-Markov process concerned is much more general than those utilized in the recent literature, which can be characterized by two important factors: (1) the transition probability matrix, and (2) the polytropical distribution functions of sojourn times. In addition, pinning scaled consensus protocol is designed by employing the pinning control technique, where only the root nodes of the union set of all the topologies are chosen to be pinned, and the final desired state value of the considered system can be realized with probability one. Finally, numerical simulations are provided to illustrate validity of the obtained main results.     

Consensus disturbance rejection with event-triggered communications

This paper considers the consensus disturbance rejection problem of networks of linear agents with event-triggered communications in the presence of matched disturbances. Based on the disturbance observer, distributed event-based consensus protocols are proposed and constructed for both the cases of neutrally stable and general linear agents. Under the proposed event-based consensus protocol, it is shown that the consensus errors are asymptotically stable and the Zeno behavior can be excluded. Compared to the previous related works, our main contribution is that the proposed event-based protocol can achieve consensus and meanwhile reject disturbance, without the need of continuous communications among neighboring agents. For the case of neutrally stable agents, the event-based protocol is fully distributed, using only the local information of each agent and its neighbors. Simulation results are presented to illustrate the effectiveness of the theoretical results.     

Distributed robust event-triggered adaptive control for a class of uncertain nonlinear multi-agent systems with actuator saturation

This paper studies the event-triggered consensus control problem for high-order uncertain nonlinear multi-agent systems with actuator saturation. By using a smooth Lipschitz function to approximate the saturation nonlinearity, an augment system and the Nussbaum function are adopted to deal with the residual terms of saturation nonlinearity based on adaptive backstepping method. Since excessive energy and communication resources will be consumed during the procedure to handle actuator saturation, two event-triggered mechanisms are proposed to save the communication resources and reduce the controllers’ update frequency. Whenever the triggered conditions are satisfied, the control signals transmitted to the actuators are updated and broadcasted to the neighboring area. A ’disturbance-like’ term is integrated so that the event-triggered control problem with actuator saturation can be transformed into a robust problem while the unknown disturbances are tackled by adaptive update laws. Moreover, the requirement for global communication topology known by all the agents is relaxed by introducing new estimators. All the signals in the closed-loop system are uniformly bounded and the consensus tracking errors are exponentially converged to a bounded set. Meanwhile, the Zeno behavior is excluded. Simulation results are employed to validate the advantages of our proposed methods.     

Distributed optimal output feedback consensus control for nonlinear Euler-Lagrange systems under input saturation

In this paper, the distributed optimal consensus control of a group of Euler-Lagrange systems under input saturation is considered. The objective function is only known by each agent itself. Meanwhile it is assumed that the velocities of the systems are unknown. To solve this problem, the filters and observers are designed for each agent. The magnitudes of the control input could be guaranteed within the bounds which are given in advance. It is shown that global optimal consensus control could be achieved under the proposed bounded controllers. The states of all agents will reach a consensus which minimizes the sum of the objective functions of all agents. Simulation results illustrate the effectiveness of the control schemes.     

Scaled consensus design for multiagent systems under DoS attacks and communication-delays

This paper aims to solve scaled consensus problem for general linear multiagent systems under denial-of-service (DoS) attacks. Firstly, we propose a new scaled disagreement vector and investigate its properties under switching and undirected graphs. Secondly, we establish sufficient conditions in terms of linear matrix inequalities in order to guarantee that the multiagent system achieves scaled consensus under DoS attacks. Contrary to most existing studies where DoS attacks on all the channels are same, in this note, we formulate the problem such that the adversary compromises each agent independently. Moreover, the distributed consensus protocol is investigated for networks with time-varying delay. Finally, two simulation examples are given to demonstrate effectiveness of the proposed design methodologies.     

Observer-based event-triggered tracking consensus of non-ideal general linear multi-agent systems

In this paper, the leader-following consensus problem of general linear multi-agent systems without direct access to real-time state is investigated. A novel observer-based event-triggered tracking consensus control scheme is proposed. In the control scheme, a distributed observer is designed to estimate the relative full states, which are used in tracking consensus protocol to achieve overall consensus. And an event-triggered mechanism with estimated state-dependent event condition is adopted to update the control signals so as to reduce unnecessary data communication. Based on the Lyapunov theorem and graph theory, the proposed event-triggered control scheme is proved to implement the tracking consensus when real-time state cannot direct obtain. Moreover, such scheme can exclude Zeno-behavior. Finally, numerical simulations illustrate the effectiveness of the theoretical results.     

Fractional-order follower observer design for tracking consensus in second-order leader multi-agent systems: Periodic sampled-based event-triggered control

This paper investigates the tracking consensus problem for the second-order leader systems by designing fractional-order observer, where a periodic sampled-based data event-triggered control is employed. In order to track the position information of leader, observers for followers are designed by fractional-order system, where only the relative position information is available. Furthermore, in the process of observers design, a sampled-based event-triggered strategy is proposed so that observers use the event-triggered sampled-data, to reduce the overall load of the network. In our proposed event-triggered strategy, the event detection only works at every sampling time instant which determines whether the sampled-data should be discarded or used. Under this control strategy, the Zeno-behavior is absolutely excluded since the minimum of inter-event times is inherently lower bounded by one sampling period. It is found that the followers can track state of the leader if fractional-order observers are appropriately designed and relevant parameters are properly selected. By using the generalized Nyquist stability criterion, a necessary and sufficient condition for the observer tracking consensus of the second-order leader systems is derived. The results show that the real and imaginary parts of the eigenvalues of the augmented Laplacian matrix, and fractional-order α of observer play a vital role in reaching consensus.     

Event-triggered control of leader-following and cluster consensus for MAS under directed graph with designable minimum event interval

This paper investigates the event-based consensus problems for linear multi-agent systems under directed network topology. First, a new event-triggered control method is proposed for the leader-following consensus problem of agents under directed graphs. Then this new method is applied to the cluster control problem under special topological conditions. The new event-based control scheme is better than some existing literature in the following aspects. 1) The graph only needs to contain a spanning tree instead of being required to be strongly connected graph or undirected, and the triggering function is state-dependent rather than time-dependent. 2) Some parameters are designable for the trade-off between the event interval and the performance of the controlled system. Besides, the optimization of some parameters is studied to reduce the trigger frequency. All the agents can achieve consensus with an exponential speed when communications among follower agents are intermittent, and Zeno behavior is excluded under the proposed method. 3) When applying this method to the cluster control problem, agents in the same cluster share the same form of triggering function. Cluster consensus can be achieved regardless of intra- and inter-cluster relative coupling strength under the event-triggered control framework.     

Sliding-mode consensus algorithms for disturbed second-order multi-agent systems

In this paper, both leaderless and leader-follower consensus problems for a class of disturbed second-order multi-agent systems are studied. Based on integral sliding-mode control, sliding-mode consensus protocols are proposed for leaderless and leader-follower multi-agent systems with disturbances, respectively. Firstly, for leaderless second-order multi-agent systems, a sliding-mode consensus protocol is proposed to make the agents achieve asymptotic consensus. Secondly, for leader-follower second-order multi-agent systems, a finite-time sliding-mode consensus protocol is designed to make the agents achieve consensus in finite time. Both kinds of consensus protocols inherit the anti-disturbance performance and robustness of sliding-mode control and require less communication information. Finally, two numerical simulations are given for leaderless and leader-follower second-order multi-agent systems to validate the efficiency of the proposed consensus protocols.     

Privacy-preserving weighted average consensus and optimal attacking strategy for multi-agent networks

This paper proposes a privacy-preserving consensus algorithm which enables all the agents in the directed network to eventually reach the weighted average of initial states, and while preserving the privacy of the initial state of each agent. A novel privacy-preserving scheme is proposed in our consensus algorithm where initial states are hidden in random values. We also develop detailed analysis based on our algorithm, including its convergence property and the topology condition of privacy leakages for each agent. It can be observed that final consensus point is independent of their initial values that can be arbitrary random values. Besides, when an eavesdropper exists and can intercept the data transmitted on the edges, we introduce an index to measure the privacy leakage degree of agents, and then analyze the degree of privacy leakage for each agent. Similarly, the degree for network privacy leakage is derived. Subsequently, we establish an optimization problem to find the optimal attacking strategy, and present a heuristic optimization algorithm based on the Sequential Least Squares Programming (SLSQP) to solve the proposed optimization problem. Finally, numerical experiments are designed to demonstrate the effectiveness of our algorithm.     

Cooperative control problem of Takagi-Sugeno fuzzy multiagent systems via observer based distributed adaptive sliding mode control

In this paper, the consensus control problem of Takagi-Sugeno (T-S) fuzzy multiagent systems (MASs) is investigated by using an observer based distributed adaptive sliding mode control. A distributed nonfragile observer is put forward to estimate the unmeasured state of agents. Based on such an observer, a novel distributed integral sliding surface is designed to suppress the disturbance and uncertainty of T-S fuzzy MASs. In order to achieve the consensus objective, a nominal distributed protocol and an adaptive sliding mode controller are separately designed. Futhermore, the nominal distributed protocol solves the consensus control problem of T-S fuzzy MASs in the absence of disturbance and uncertainty by using the information of adjacent agents obtained by the observer, while the adaptive sliding mode controller suppresses the disturbance and uncertainty. Finally, the proposed method is applied to two examples. Example 1 verifies the superiority of the method by comparing with the fuzzy-based dynamic sliding mode controller. Example 2 is used to illustrate that our control scheme can effectively solve the consensus control problem of T-S fuzzy MASs.     

A new class of fixed-time bipartite consensus protocols for multi-agent systems with antagonistic interactions

In this paper, we study the fixed-time consensus problem for multi-agent systems with structurally balanced signed graph. A new class of fixed-time nonlinear consensus protocols is designed by employing the neighbor’s information. By using Lyapunov stability method, states of all agents can be guaranteed to reach agreement in a fixed time under our presented protocols, and the consensus values are the same in modulus but different in sign. Moreover, it is shown that the settling time is not dependent on the initial conditions, and it makes a good convenience to estimate the convergence time by just knowing the graph topology and the information flow of the multi-agent systems. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed consensus protocols.     

Event-Triggered privacy-preserving average consensus for continuous-time multi-agent network systems

This paper deals with the privacy-preserving average consensus problem for continuous-time multi-agent network systems (MANSs) based on the event-triggered strategy. A novel event-triggered privacy-preserving consensus algorithm is designed to achieve the average consensus of MANSs while avoiding the disclosure of the agents’ initial states. Different from the approaches incorporating stochastic noises, an output mask function in the proposed algorithm is developed to make initial state of each agent indiscernible by the others. Particularly, under the output mask function, all agents can exactly tend to the average value of initial states rather than the mean square value. Under the proposed algorithm, detailed theoretical proof about average consensus and privacy of the MANSs are conducted. Moreover, the proposed algorithm is extended to nonlinear continuous-time MANSs, and the corresponding results are also derived. A numerical simulation eventually is performed to demonstrate the validity of our results.     

Event-triggered learning consensus of networked heterogeneous nonlinear agents with switching topologies

In this work, a lifted event-triggered iterative learning control (lifted ETILC) is proposed aiming for addressing all the key issues of heterogeneous dynamics, switching topologies, limited resources, and model-dependence in the consensus of nonlinear multi-agent systems (MASs). First, we establish a linear data model for describing the I/O relationships of the heterogeneous nonlinear agents as a linear parametric form to make the non-affine structural MAS affine with respect to the control input. Both the heterogeneous dynamics and uncertainties of the agents are included in the parameters of the linear data model, which are then estimated through an iterative projection algorithm. On this basis, a lifted event-triggered learning consensus is proposed with an event-triggering condition derived through a Lyapunov function. In this work, no threshold condition but the event-triggering condition is used which plays a key role in guaranteeing both the stability and the iterative convergence of the proposed lifted ETILC. The proposed method can reduce the number of control actions significantly in batches while guaranteeing the iterative convergence of tracking error. Both rigorous analysis and simulations are provided and confirm the validity of the lifted ETILC.     

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