Consensus Tracking Of Multi-agent Systems Research Articles

Average Consensus Tracking of Weight-Balanced Multi-Agent Systems via Sampled Data

This paper studies the average consensus tracking problem of first-order multi-agent systems under directed topologies. A control protocol is constructed based on the neighbors’ agent sampled information. With the help of the matrix theory and frequency domain analysis, the necessary and sufficient condition can be induced for the average consensus tracking of multi-agent systems, although the weight-balanced condition is not satisfied. In addition, a numerical simulation example is given to illustrate the effectiveness of the proposed results.

SMC-Based Bounded Consensus Tracking for Multiagent Systems Under Stochastic DoS Attacks With Applications to Multiple DC Motors

SMC-Based Bounded Consensus Tracking for Multiagent Systems Under Stochastic DoS Attacks With Applications to Multiple DC Motors

Event-based [formula omitted] consensus tracking for multi-agent systems under switching networks

This paper systematically investigates consensus tracking of linear multi-agent systems with disturbances over directed switching topologies. Both state and output feedback H∞ controllers are jointly synthesized with the triggering mechanism. First, a state-based event-triggered H∞ controller design for achieving consensus tracking is carried out, which can result in settling the occurrence of disturbances and the reduction of controller updates as well as averting Zeno behavior. Considering the case that only output information of agent is required, an event-triggered H∞ output feedback controller is then proposed and sufficient condition for the solvability of consensus tracking problem are also derived. Compared with the existing results, the effects of disturbances on directed switching topologies can be tackled when continuous communication and full-state information of the agent are not needed. Numerical simulation are finally conducted to illustrate the effectiveness of the proposed methods.

An Adaptive Continuous Approach to Consensus Tracking of Nonlinear Multiagent Systems With a Nonautonomous Leader

It is challenging and critical to achieve zero error consensus tracking in multiagent systems (MASs) with nonautonomous leaders (i.e., leaders with nonzero inputs). The traditional approach is to use discontinuous controllers which may cause a chattering phenomenon. How to achieve zero error consensus tracking via a chattering-free controller is still open. We propose a class of adaptive continuous controllers to achieve zero error consensus tracking for Lipschitz nonlinear MASs with a nonautonomous leader and directed communication topology. Unlike existing works that use discontinuous functions to eliminate the impacts of leaders’ inputs, we use a continuous function by introducing an exponential decay function into the denominator. First, we design a continuous controller with fixed coupling strengths and prove that zero error consensus tracking can be achieved if the coupling strengths are greater than some positive constants. Second, we design a continuous controller with dynamic coupling strengths under which fully distributed zero error consensus tracking can be achieved. Moreover, the case with undirected communication topology is studied. Finally, three examples are given to verify the theoretical results. Specifically, convergence results between the continuous controller here and that is developed via the boundary layer technique are compared. Compared with existing works, the designed adaptive continuous controllers here can not only achieve zero error consensus tracking but also is chattering free.

Fault estimation and consensus tracking of multi-agent systems based on intermediate estimator

The consensus tracking of multi-agent systems (MASs) with process and sensor faults is investigated in this paper. First, process faults are taken into account, and an intermediate estimator is designed to estimate the system states and faults. By formulating appropriate Lyapunov functions, some sufficient conditions are derived to ensure the consensus tracking of MASs. Subsequently, the obtained results are extended to the case that both process and sensor faults occur in MASs. Leveraging the estimated system states and faults, an unique control protocol is proposed to achieve the consensus tracking of MASs and effectively compensate for process faults. The obtained theoretical results are demonstrated and verified by two simulation examples.

Neural Network-Based Robust Bipartite Consensus Tracking Control of Multi-Agent System with Compound Uncertainties and Actuator Faults

This paper addresses the challenging problem of bipartite consensus tracking of multi-agent systems that are subject to compound uncertainties and actuator faults. Specifically, the study considers a leader agent with fractional-order nonlinear dynamics unknown to the followers. In addition, both cooperative and competitive interactions among agents are taken into account. To tackle these issues, the proposed approach employs a fully distributed robust bipartite consensus tracking controller, which integrates a neural network approximator to estimate the uncertainties of the leader and the followers. The adaptive laws of neural network parameters are continuously updated online based on the bipartite consensus tracking error. Furthermore, an adaptive control technique is utilized to generate the fault-tolerant component to mitigate the partial loss caused by actuator effectiveness faults. Compared with the existing works on nonlinear multi-agent systems, we consider the compound uncertainties, actuator faults and cooperative–competition interactions simultaneously. By implementing the proposed control scheme, the robustness of the closed-loop system can be significantly improved. Finally, numerical simulations are performed to validate the effectiveness of the control scheme.

Secure consensus tracking of multi-agent systems with network-induced delays under deception attacks via guaranteed performance impulsive control

Secure consensus tracking of multi-agent systems with network-induced delays under deception attacks via guaranteed performance impulsive control

Prescribed-Time Consensus Tracking of Multiagent Systems With Nonlinear Dynamics Satisfying Time-Varying Lipschitz Growth Rates.

Prescribed-time consensus tracking for second-order nonlinear multiagent systems (MASs) with the unknown nonlinear dynamics satisfying a time-varying Lipschitz growth rate is investigated in this article. A time-varying function is introduced as a part of the controller gains, and it plays an important role in overcoming the rapid growth of nonlinear terms and in ensuring that the consensus can be achieved in a preassigned time. An integral sliding-mode control protocol, which forces the system trajectory to move on to the defined sliding manifold at the initial moment, is proposed for solving the prescribed-time consensus tracking problem of leader-following MASs with disturbances. Furthermore, we propose a slightly different control law based on terminal sliding-mode control, and under such a controller, the trajectories of each follower reach the sliding manifold in an arbitrary assigned time T1 , and then in a specified time T2 , the position and velocity tracking errors for all followers converge to 0 at the same time instant. Based on the graph theory, state transformations, and Lyapunov theorem, we prove that the proposed solutions are feasible and, finally, three simulation examples are provided to verify the theoretical results.

Fixed-Time Consensus Tracking for Multi-Agent Systems With a Nonholomonic Dynamics

In this article, we investigate the control strategy of fixed-time leader-following consensus for chained-form systems with matched disturbances. A new decentralized observer is designed under a directed topology to estimate the leader state in a fixed time for each follower. Then, a novel control protocol is developed to track the estimated leader state in a prescribed finite time. Different from existing results, the bound we derive for the setting time does not depend on the initial conditions even in the presence of matching perturbations. Moreover, the chattering phenomenon of control output is effectively reduced as signum function gets smaller in the proposed method.

Practical bipartite consensus for multi-agent systems: A barrier function-based adaptive sliding-mode control approach

This paper is concerned with bipartite consensus tracking for multi-agent systems with unknown disturbances. A barrier function-based adaptive sliding-mode control (SMC) approach is proposed such that the bipartite steady-state error is converged to a predefined region of zero in finite time. Specifically, based on an error auxiliary taking neighboring antagonistic interactions into account, an SMC law is designed with an adaptive gain. The gain can switch to a positive semi-definite barrier function to ensure that the error auxiliary is constrained to a predefined neighborhood of zero, which in turn guarantees practical bipartite consensus tracking. A distinguished feature of the proposed controller is its independence on the bound of disturbances, while the input chattering phenomenon is alleviated. Finally, a numerical example is provided to verify the effectiveness of the proposed controller.

Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults

Consensus Tracking of Multi-Agent Systems in Presence of Uncertain Dynamics and Communications Faults

Exponential output consensus tracking for multi-agent systems with uncertain local output function via sampled communication

In this paper, the output consensus tracking problem is investigated for heterogeneous multi-agent systems (MASs) with asynchronous sampled communication, where only local output of the leader is required and the local output function contains an unknown parameter. A distributed adaptive observer is designed for recovering the leader’s state and unknown parameter, which has three features: (i) two predictors are contained in the observer to recover the output injection and the consensus error separately; (ii) by designing proper gain matrices, the state estimation is decomposed into the detectable part merely using the sampled local output of the leader and the undetectable part only using sampled information of the neighbors; (iii) the negative effect of the parameter estimation errors is offset by adding complementary terms with coupled auxiliary variables into the observer. Based on the observer, the control scheme is provided to realize the exponential output consensus tracking. It is shown that the maximal sampling period for the follower to receive local output from the leader is independent of the neighbors.

Distributed state estimator-based consensus tracking of multi-agent systems with exogenous disturbance

The consensus tacking problem for multi-agent systems with a leader of none control input and unknown control input is studied in this paper. By virtue of the relative state information of neighboring agents, state estimator and disturbance estimator are designed for each follower to estimate the system states and exogenous disturbance, respectively. Meanwhile, a novel control protocol based on two estimators is designed to make tracking error eventually converge to zero. Furthermore, the obtained results are further extended to the leader with unknown control input. A novel state estimator with adaptive time-varying gain is proposed such that consensus tracking condition is independent of the Laplacian matrix with regard to the communication topology. Finally, two examples are presented to verify the feasibility of the proposed control protocol.

Nonlinear finite-time and fixed-time bipartite consensus tracking of multi-agent systems

ABSTRACT This paper deals with the finite-time and fixed-time bipartite consensus tracking (FFBCT) problems for multi-agent systems (MASs) , in which both cooperative and competition exist. Using Lyapunov stability methods, distributed nonlinear protocols are provided to ensure all agents reach agreement. Its absolute value is the same but it might be different in direction. Besides, the second protocol can make the system reach bipartite consensus in fixed time regardless of the initial state of agents. Moreover, boundaries for settling times are estimated. Some numerical examples are finally presented to prove the validity of our designs.

Distributed Fault-Tolerant Consensus Tracking of Multi-Agent Systems Under Cyber-Attacks

This paper investigates the distributed fault-tolerant consensus tracking problem of nonlinear multi-agent systems with general incipient and abrupt time-varying actuator faults under cyber-attacks. First, a decentralized unknown input observer is established to estimate relative states and actuator faults. Second, the estimated and output neighboring information is combined with distributed fault-tolerant consensus tracking controllers. Criteria of reaching leader-following exponential consensus tracking of multi-agent systems under both connectivity-maintained and connectivity-mixed attacks are derived with average dwelling time, attack frequency, and attack activation rate technique, respectively. Simulation example verifies the effectiveness of the fault-tolerant consensus tracking algorithm.

Fixed-Time Practical Consensus Tracking of Multi-Agent Systems With Communication Delay

This paper addresses the fixed-time consensus tracking problem for second-order multi-agent systems (MASs) subjected to communication delays under directed communication network. First, a predictive algorithm is designed to predict the neighbors’ states at current time by using the delayed information. Next, based on the predicted neighbor's states, a fixed-time distributed observer is developed to estimate the leader's states. Finally, a predefined-time nonsingular terminal sliding mode control is proposed to stabilize the tracking error system and we can determine the controller gain as soon as the convergence time bound is prescribed. It is rigorously proved that the presented scheme achieves fixed-time consensus tracking of the studied MASs. This study contributes to providing a solution to fixed-time consensus tracking problem of second-order MASs subjected to communication delays under directed communication network, which is a challenging and important issue that has not been studied. The effectiveness of the presented strategy is validated through simulation results.

Hybrid Event-Triggered Consensus Tracking of Multi-Agent Systems With Discrete Control Update

This brief considers the leader-following consensus (consensus tracking) problem of multi-agent systems (MAS) with event-triggered communication. A novel hybrid event-triggering mechanism is proposed to reduce the burden of network transmission, and it is ensured that Zeno behavior does not occur. Besides, it is required that the control protocol is only updated at agent’s own triggering instant. Compared with the existing works, the main contribution is that the minimum inter-event time (MIET) can be pre-specified, which is important for physical implementation, and the control update frequency is also reduced. An example is given to verify the correctness of the proposed hybrid event-triggered control strategy.

Adaptive sliding mode controller design for the bipartite consensus tracking of multi-agent systems with actuator faults and disturbances

This paper studies the bipartite consensus problem for second-order nonlinear multi-agent systems in the presence of actuator faults, unknown control gains and unknown external disturbances. The actuator faults are considered as partial loss of effectiveness fault and bias fault. For design controller, the control gains and disturbances only need to have unknown upper bounds. Also a signed bipartite directed graph is used for describing the communication topology of the multi-agent system. An adaptive sliding mode controller is developed for bipartite consensus tracking of the multi-agent system. The proposed adaptive sliding mode controller ensures the uniformly ultimately bounded cooperative tracking of the multi-agent system. Finally, the correctness and effectiveness of the proposed control method is verified via simulation results.

Adaptive sliding mode controller design for the bipartite consensus tracking of multi-agent systems with actuator faults and disturbances

Adaptive sliding mode controller design for the bipartite consensus tracking of multi-agent systems with actuator faults and disturbances

Adaptive MLP neural network controller for consensus tracking of Multi-Agent systems with application to synchronous generators

In this study a novel cooperative controller design is developed to tackle the consensus tracking problem of Multi-Agent systems (MAS) based on multilayer perceptron neural network (MLPNN), applied on a distributed synchronous generator (SG) Multi-Agent system in presence of model uncertainties and external disturbances. Application of MLPNN in controller design can lead to smoother system response and can neutralize the impacts of model uncertainties. Furthermore, the proposed method benefits from a novel algorithm formerly known as error backpropagation (BP) algorithm to update and to regulate the weights of MLPNN adaptively based on the principles of consensus error. The proposed strategy can be very effective in control of the distributed SG Multi-Agent system due to its ability for system identification, parameter estimation, and disturbance approximation. Moreover, the utilization of neural networks can meet the criterion to make the consensus error uniformly ultimately bounded. Ultimately, simulation results illustrate the applicability and effectiveness of the novel MLPNN controller to model the system uncertainties and to deal with external disturbances of the distributed SG Multi-Agent system.