Adaptive consensus control for output-constrained nonlinear multi-agent systems with actuator faults

This paper addresses the problem of leader-follower consensus fault-tolerant control for a class of nonlinear multi-agent systems with output constraints. Specifically, a new nonlinear state transformation function is proposed to deal with the asymmetric constraint on output. Moreover, by integrating backstepping and radial basis function neural network approaches, an adaptive consensus control framework is developed with a single parameter estimator, which mitigates the computation of control algorithm in comparison with conventional adaptive approximation based control techniques. Then an adaptive compensation method is proposed to eliminate the effect of actuator failure. Under the proposed control scheme, all the closed-loop signals of the systems are bounded and the consensus tracking error converges to an adjustable small neighborhood of zero. To evaluate the developed control algorithm, a group of four networked two-stage chemical reactors is used to illustrate the effectiveness of the theoretic results obtained.     

Finite-time consensus control for a class of multi-agent systems with dead-zone input

This paper investigates a finite-time consensus issue for non-affine pure-feedback multi-agent systems with dead-zone input. Compared with the existing results on multi-agent systems, finite-time consensus problem of non-affine multi-agent systems is proposed for the first time. Based on the backsteppting technique, adaptive finite-time consensus control scheme is presented. With the help of this strategy, adaptive virtual variables, adaptive laws and the actual controller are designed to guarantee that the consensus errors converge to a small scale of the origin in finite time. Finally, a practical example is applied to verify the feasibility of the proposed method.     

Formation consensus for discrete-time heterogeneous multi-agent systems with link failures and actuator/sensor faults

In this paper, a distributed control protocol is presented for discrete-time heterogeneous multi-agent systems in order to achieve formation consensus against link failures and actuator/sensor faults under fixed and switching topologies. A model equivalent method is proposed to deal with the heterogeneous system consists of arbitrary order systems with different parameters. Based on graph theory and Lyapunov theory, stability conditions to solve formation consensus problem are developed for the underlying heterogeneous systems with communication link failures. In order to tolerate actuator/sensor faults, a distributed adaptive controller is proposed based on fault compensation. The desired control is designed by linear matrix inequality approach together with cone complementarity linearisation algorithm. After applying the new control scheme to heterogeneous systems under the directed topologies with link failures and faults, the resulting closed-loop heterogeneous system is validated to be stable. The effectiveness of the new formation consensus control strategy and its robustness are verified by simulations.     

Event-based consensus for second-order multi-agent systems with actuator saturation under fixed and Markovian switching topologies

This paper studies the event-based consensus problem of second-order multi-agent systems with actuator saturation under fixed topology and Markovian switching topologies. By a model transformation, the consensus problem is first converted into the stability problem of the error system. Using discontinuous Lyapunov functional approach, two sufficient conditions on the consensus are derived for second-order multi-agent systems with fixed topology and Markovian switching topologies, respectively. The discontinuous Lyapunov functions take full account of the characteristics of the sawtooth delay, and thus lead to a less conservative consensus criterion. It is shown that the consensus condition depends on the parameters of sampling period, Laplacian matrix, and event-triggered parameter. In addition, this paper provides an effective method to co-design both the consensus controller and the event-triggered parameter. Finally, two numerical examples are provided to illustrate the effectiveness and feasibility of the proposed algorithm.     

Consensus of multi-agent systems with Luenberger observers

This paper studies the consensus problem of the multi-agent systems with parallel Luenberger observers. First, the structure of the cooperative system is established, where the output of the built-in Luenberger observer for each agent is used as its local control input and the cooperative control input combining with the cooperative measurement output is utilized as the input of the observers. Based on the structure of the closed-loop system, the consensus problem is then analyzed. In addition, two methods for designing the controller gains are provided. By virtue of the proposed structure, it is pointed out that the design of the controller gains and the observer parameters can be carried out separately. Finally, by resorting to the gradient flow method, an optimization algorithm is proposed to reduce the influence of the environmental noises. The effectiveness of the obtained results is shown through a numerical example.     

Dynamic event-Based resilient consensus of networked lagrangian systems under DoS attacks

In this paper, the dynamic event-based resilient consensus control of the multiple networked Euler-Lagrangian (E-L) systems under the Denial of Service (DoS) attacks is considered. Compared with linear cyber-physical systems, nonlinear networked E-L systems are more complex and closer to actual mechanical systems. For the situation where the topology is a strongly connected directed topology, a controller based on a dynamic event-trigger mechanism is designed to achieve consensus control for the networked E-L system in the absence of DoS attacks. Sufficient conditions are presented, which can guarantee the closed-loop system be stable. Then the resilient consensus problem of event-based controllers under energy-constrained DoS attacks is analyzed. The conditions related to the duration and frequency of DoS attacks are given. Zeno behavior is proved does not exist in the proposed control scheme. Finally, some numerical simulation results are given for verifying the theoretical results.     

Distributed event-triggered adaptive finite-time consensus control for second-order multi-agent systems with connectivity preservation

In this paper, we consider the robust finite-time consensus problem for second-order multi-agent systems (MASs) with limited sensing range and weak communication ability. As a stepping stone, a novel distributed finite-time sliding mode manifold is developed for MASs. Then, by combining artificial potential function technique with the presented sliding mode manifold, a robust distributed control scheme is proposed to enable the finite-time consensus of MASs while preserving the prescribed communication connectivity. Furthermore, the sampling frequency and implementation burden of the proposed controller can be reduced with resort to the event-triggered methodology. Finally, numerical examples are given to show the effectiveness of the proposed method.     

Consensus of networked multi-agent systems via the networked predictive control and relative outputs

This paper investigates the consensus problem of discrete-time networked multi-agent systems (DNMASs) with a directed topology and communication delay, where exact state and output of each agent are not measured, and yet output differences between agent and its neighboring ones (relative outputs for short) are available. Based on the networked predictive control scheme and relative output data, a novel protocol is proposed to overcome the effect of delay on the consensus actively. Moreover, for the DNMASs with a fixed topology and constant communication delay, delay-independent necessary and/or sufficient conditions of achieving consensus are obtained, which reveal that the essence of dominating the consensus is agents' dynamics and communication topology. Simulation results further demonstrate the effectiveness of theoretical results.     

Leader-following consensus of multi-agent systems with limited data rate

This paper investigates the leader-following consensus problem of time-invariant linear multi-agent systems with limited data rate. Based on the idea of assigning a priority level for each agent of the concerned multi-agent system, a novel distributed control law has been proposed. The proposed control law has two distinctive advantages. That is, it is fully distributed in the sense that it does not rely on the eigenvalues of the Laplace matrix associated with the topology. Moreover, the required data rate is independent of the number of agents and remains small even if the number of the agents in multi-agent systems is large. An example is finally given to illustrate the effectiveness of the proposed controller.     

Consensus of multi-agent systems with both input amplitude and input rate constraints

In this paper, the consensus problem is considered for multi-agent systems with input constraint under directed graphs, including leaderless and leader-following cases. Different from existing related works, the distinct feature of this paper is that both the amplitude and rate of the agents’ input are ensured in the given ranges. For the leaderless case, the saturation control strategy is designed and employed for multi-agent systems consensus with the aid of a novel saturation function. For the leader-following case, the saturation-function-based distributed observer as well as the observer-based saturation controller are proposed to achieve consensus. Finally, simulation results show the effectiveness of the designed methods.     

Leaderless consensus of multi-agent systems via an event-triggered strategy under stochastic sampling

This paper investigates mean square leaderless consensus of networked nonlinear multi-agent systems. An efficient distributed event-triggered mechanism based on stochastic sampling is introduced to reduce the communication cost and controller updates. The stochastic sampling interval randomly switches between two given values. Mean square consensus criteria for multi-agent systems with strongly connected networks or networks containing directed spanning trees are derived, respectively. Moreover, the case with a special event-triggered weighting matrix and the case without even-triggered strategies are also discussed. Finally, an example is given to verify the theoretical results.     

Fixed-time bipartite consensus of nonlinear multi-agent systems using event-triggered control design

This paper focuses on designing a leader-following event-triggered control scheme for a category of multi-agent systems with nonlinear dynamics and signed graph topology. First, an event-triggered controller is proposed for each agent to achieve fixed-time bipartite consensus. Then, it is shown that the Zeno-behavior is rejected in the proposed algorithm. To avoid intensive chattering due to the discontinuous controller, the control protocol is improved by estimating the sign function. Moreover, a triggering function is proposed which avoids continuous communication in the event-based strategy. Finally, numerical simulations are given to show the accuracy of the theoretical results.     

Cooperative localization and circumnavigation of multiple targets with bearing-only measurements

This paper studies the multi-target localization and circumnavigation problem for a networked multi-agent system using bearing-only measurements. A more general case that only some of the agents are responsible for measuring the bearing angles with respect to the targets is considered. First, a novel estimator is developed for the agents to locate the targets collaboratively, based on which the geometric center of multi-target is reconstructed by each agent. Then, an estimator-based distributed controller is proposed to steer the agents, such that they can enclose the targets along different circles centered at the geometric center of multi-target with any desired angular spacing. By using Lyapunov stability theory, graph theory and consensus algorithm, global exponential stability of the overall system is analyzed rigorously. Besides, it is proved that bounded angular velocity of each agent and collision avoidance between the target and agent can be guaranteed in the whole movement process. Finally, numerical simulations are given to corroborate the theoretical results.     

Leader-following rendezvous for uncertain Euler–Lagrange multi-agent systems by output feedback

In this paper, we investigate the problem of output feedback tracking for a class of Euler–Lagrange multi-agent systems with unmeasurable velocity and input disturbances. By proposing a novel dynamic velocity observer, an adaptive output feedback consensus algorithm is proposed such that the tracking errors of all agents can converge to an arbitrarily small neighborhood of zero by tuning the design parameters. A numerical example is presented to illustrate the effectiveness of the controller.     

Consensus-based distributed fixed-time optimization for a class of resource allocation problems

A class of resource allocation problems with equality constraint are considered in this paper, such as economic dispatch problem in smart grid systems, which is essentially an optimization problem. Inspired by the Lagrange multiplier method, the resource allocation problem is transformed into a multi-agent consensus problem for large-scale networked distributed nodes. A consensus-based distributed fixed-time optimization algorithm is presented, where the information exchange network is depicted by a strongly connected and weight-balanced digraph. This type of communication network can ensure that the equality constraint always holds. Moreover, a new globally fixed-time stability theorem for nonlinear systems is first given in this paper. Based on this theorem and consensus theory, the optimal resource allocation scheme can be given in a fixed time. Finally, the application and comparison of the designed algorithm show that the algorithm can effectively solve the allocation problem of power resources such as economic dispatch.     

Finite-time formation control of nonaffine nonlinear systems under directed communication interactions

This paper studies the problem of finite-time formation tracking control for networked nonaffine nonlinear systems with unmeasured dynamics and unknown uncertainties/disturbances under directed topology. A unified distributed control framework is proposed by integrating adaptive backstepping control, dynamic gain control and dynamic surface control based on finite-time theory and consensus theory. Auxiliary dynamics are designed to construct control gains with non-Lipschitz dynamics so as to guarantee finite-time convergence of formation errors. Adaptive control is used to compensate for uncertain control efforts of the transformed systems derived from original nonaffine systems. It is shown that formation tracking is achieved during a finite-time period via the proposed controller, where fractional power terms are only associated with auxiliary dynamics instead of interacted information among the networked nonlinear systems in comparison with most existing finite-time cooperative controllers. Moreover, the continuity of the proposed controller is guaranteed by setting the exponents of fractional powers to an appropriate interval. It is also shown that the improved dynamic surface control method could guarantee finite-time convergence of formation errors, which could not be accomplished by conventional dynamic surface control. Finally, simulation results show the effectiveness of the proposed control scheme.     

Leader-following consensus control for semi-Markov jump multi-agent systems: An adaptive event-triggered scheme

The problem of event-triggered leader-following consensus control for semi-Markov multi-agent systems is investigated in this paper. A semi-Markov process is used to describe the sudden parameter changes between every agent. An adaptive event-triggered control strategy is proposed to make a balance between reducing unnecessary communication and meeting the required performance. A control protocol which can resist actuator faults is used to ensure the reliable leader-following consensus. By employing the Lyapunov–Krasovskii functional method, some sufficient conditions are provided to guarantee that the leader-following consensus can be achieved in mean-square sense. The consensus controller and the event-triggered parameter can be co-designed. Finally, the effectiveness of the proposed method is verified by a F-404 aircraft engine system.     

Distributed control for output-constrained nonlinear multi-agent systems with completely unknown non-identical control directions

This paper studies the consensus problem for a class of nonlinear multi-agent systems with asymmetric time-varying output constraints and completely unknown non-identical control directions. Firstly, in order to deal with the problem of asymmetric time-varying output constraints, the original output-constrained multi-agent systems are transformed into new unconstrained multi-agent systems by constructing the state transformation for each agent. Secondly, the emergence of multiple Nussbaum-type function terms is avoided by introducing novel sliding-mode-esque auxiliary variables and consensus estimate variables, which allows the control directions to be completely unknown non-identical. Thirdly, a novel control strategy is proposed by combining novel variables with state transformation method for the first time, which makes the design of distributed consensus protocol more concise. Through Lyapunov stability analysis, the proposed distributed protocol ensures that the output constraints are never violated and the consensus can be achieved asymptotically. Finally, a practical simulation example is given to demonstrate the effectiveness of the proposed distributed consensus protocol.     

Distributed control of cluster lag consensus for first-order multi-agent systems on QUAD vector fields

This paper addresses the problem of cluster lag consensus for first-order multi-agent systems which can be formulated as moving agents in a capacity-limited network. A distributed control protocol is developed based on local information, and the robustness of the protocol is analyzed by using tools of Frobenius norm, Lyapunov functional and matrix theory. It is shown that when the root agents of the clusters are influenced by the active leader and the intra-coupling among agents is stronger enough, the multi-agent system will reach cluster lag consensus. Moreover, cluster lag consensus for multi-agent systems with a time-varying communication topology and heterogeneous multi-agent systems with a directed topology are studied. Finally, the effectiveness of the proposed protocol is demonstrated by some numerical simulations.     

Consensus control via iterative learning for distributed parameter models multi-agent systems with time-delay

Most of the available results of iterative learning control (ILC) are that solve the consensus problem of lumped parameter models multi-agent systems. This paper considers the consensus control problem of distributed parameter models multi-agent systems with time-delay. By using the knowledge between neighboring agents, considering time-delay problem in the multi-agent systems, a distributed P-type iterative learning control protocol is proposed. The consensus error between any two agents in the sense of L² norm can converge to zero after enough iterations based on proposed ILC law. And then we extend these conclusions to Lipschitz nonlinear case. Finally, the simulation result shows the effectiveness of the control method.