Consensus Control For Multi-agent Systems Research Articles

Distributed Event-Triggered Fault-Tolerant Consensus Control of Multi-Agent Systems Under DoS Attacks

Distributed Event-Triggered Fault-Tolerant Consensus Control of Multi-Agent Systems Under DoS Attacks

PDE Based Consensus Control for Multi-agent Systems with Event-triggered Mechanism

PDE Based Consensus Control for Multi-agent Systems with Event-triggered Mechanism

Self-Triggered Consensus Control of Multi-Agent Systems From Data

Self-Triggered Consensus Control of Multi-Agent Systems From Data

Fixed-Time Group Consensus Control of Multi-Agent Systems With Actuator Faults Based on Dynamic Event Triggering

Fixed-Time Group Consensus Control of Multi-Agent Systems With Actuator Faults Based on Dynamic Event Triggering

Adaptive Neural Consensus of Unknown Non-Linear Multi-Agent Systems with Communication Noises under Markov Switching Topologies

In this paper, the adaptive consensus problem of unknown non-linear multi-agent systems (MAs) with communication noises under Markov switching topologies is studied. Based on the adaptive control theory, a novel distributed control protocol for non-linear multi-agent systems is designed. It consists of the local interfered relative information and the estimation of the unknown dynamic. The Radial Basis Function networks (RBFNNs) approximate the nonlinear dynamic, and the estimated weight matrix is updated by utilizing the measurable state information. Then, using the stochastic Lyapunov analysis method, conditions for attaining consensus are derived on the consensus gain and the weight of RBFNNs. The main findings of this paper are as follows: the consensus control of multi-agent systems under more complicated and practical circumstances, including unknown nonlinear dynamic, Markov switching topologies and communication noises, is discussed; the nonlinear dynamic is approximated based on the RBFNNs and the local interfered relative information; the consensus gain k must to be small to guarantee the consensus performance; and the proposed algorithm is validated by the numerical simulations finally.

Secured consensus control for multi-agent systems under DoS attacks: Coding–decoding communication protocol

This paper focuses on the leader following consensus control problem for multi-agent systems (MASs) subject to denial-of-service (DoS) attacks. First, a sliding mode observer is developed to estimate each agent state, actuator, and sensor fault. Then, a coding–decoding communication protocol is proposed to enhance the communication security between agents. Based on the sliding mode observer and communication protocol, a leader-following consensus controller is designed to guarantee the consensus and input-to-state stability of MASs under DoS attacks. Finally, the effectiveness of the developed controller is verified by a simulation example.

Distributed Optimal Consensus Control of Multiagent Systems Involving State and Control Dependent Multiplicative Noise

This paper aims to solve the multi-objective optimization control problem by investigating the consensus problem of multi-agent simultaneous optimization with state and control dependent multiplicative noise. The main contributions of this work are two-fold. First, the optimal consensus control problem is solved by designing the free item of an optimal controller, and the coefficient of the feedback gain is obtained based on analyzing a parameterized generalized algebraic Riccati equation. Second, we derive a new consensus controller that comprises two parts different from the current consensus. One part minimizes a linear quadratic index with a singular control weighting matrix, and the other affords the multi-agent systems to achieve mean square consensus.

Consensus Control of Multiagent Systems Under Switching Topology and Denial-of-Service Attacks

This article studies the consensus problem of multiagent systems (MASs) under denial-of-service (DoS) attacks and switching topology. Compared with the previous papers, under the switching topology, the impact of DoS attacks on the MAS is considered, and thus, the difficulty of consensus protocol design is further increased. First, a piecewise resilient consensus protocol is proposed to ensure that the MAS can achieve consensus under switching topology and DoS attacks. Then, by considering the different convergence rates caused by the switching topology in each sleep period of DoS attacks, a piecewise Lyapunov–Krasovskii function is established. The sufficient conditions on the global convergence of the system are obtained under switching topology and DoS attacks. In the meantime, the lower bound of average dwell time of the switching topology is determined under DoS attacks. The relationship between average dwell time and the parameters of DoS attacks is discussed. Finally, the simulation example is conducted to verify the effectiveness of the proposed method.

Adaptive fault-tolerant consensus control of multi-agent systems with event-triggered inputs

Adaptive fault-tolerant consensus control of multi-agent systems with event-triggered inputs

Security consensus control for multi-agent systems under DoS attacks via reinforcement learning method

This paper is concerned with the security consensus control issue for discrete-time multiagent systems (MASs) on the basis of a reinforcement learning (RL) approach. Considering the effects of denial-of-service (DoS) attacks, a novel control protocol is proposed to deal with the H∞ consensus problem. Firstly, a Q-learning algorithm is put forward under the directed graph, which can obtain the target gain matrices without any system dynamics information. In addition, the obtained gain matrices and Lyapunov function are employed to demonstrate that the MASs can reach security consensus. Moreover, the proof of H∞ consensus under undirected graphs is derived using the designed Q-learning algorithm. In the end, the simulation experiments are given to verify the correctness of the designed control strategy.

Adaptive fuzzy prescribed settling time consensus control for multi-agent systems with input hysteresis via dynamic event-triggered mechanism

An adaptive fuzzy prescribed settling time consensus control is proposed based on the dynamic event-triggered mechanism for a class of uncertain nonlinear multi-agent systems (UNMASs) subject to input hysteresis. In practical systems, the plant inevitably suffers from input hysteresis and unknown nonlinear characteristics, which dramatically deteriorate its performance. Therefore, to eliminate the effects of those constraints, an adaptive fuzzy prescribed settling time control scheme is constructed by applying backstepping technique and first-order filter. Wherein each agent needs to be equipped with only one adaptive law for fuzzy-logic-system approximation, reducing the computational burden. Simultaneously, the synchronization error is mapped using a transformation function to achieve prescribed settling time consensus control. Moreover, a dynamic event-triggered mechanism is employed to reduce unnecessary communication transmission and save energy. With the presented method, all agents synchronize to the virtual leader within a prescribed settling time. Theoretical analysis and simulation examples verify the presented method.

Sliding mode consensus control for multi-agent systems under multi-node round-robin protocol

This work investigates the consensus issue for nonlinear multi-agent systems (MASs) via the multi-node round-robin protocol (MRRP) and sliding mode control (SMC) method. The MRRP is used to schedule information transmissions among agents. On the one hand, considering the limited communication ability of the leader, the leader could take turns sending information to several nearby followers. On the other hand, for reasonably scheduling communication resources among followers, the number of follower’s sensor nodes could be automatically adjusted to transmit their information according to the size of the consensus error. Under the MRRP, a token-dependent sliding mode controller is designed to achieve consensus. And controller gains are obtained via the optimized algorithm. Eventually, two numerical simulation instances are furnished to substantiate the efficacy of the proposed SMC strategy under MRRP.

Adaptive Iterative Learning Fault-Tolerant Consensus Control of Multiagent Systems Under Binary-Valued Communications.

In this article, the iterative learning averaging consensus problem is studied for multiagent systems with system uncertainties, actuator faults, and binary-valued communications. Considering only binary-valued measurement information with stochastic noise can be received from its neighbors for each agent, a new two-iteration-scale framework that alternates estimation and control is designed. Under the proposed framework, each agent estimates the neighbors' states based on the empirical measurement method during a dwell iteration interval, during which each agent's states will keep constant along the iteration axis. Further, in view of the impacts of system uncertainties and actuator faults, a novel adaptive iterative learning fault-tolerant averaging consensus control scheme is designed based on its own states and the estimated neighbors' states. Finally, the resulting closed-loop system is rigorously proved to be stable, and numerical simulations are conducted to demonstrate the effectiveness of the developed control strategy.

HDWM-based Consensus Control for Multi-agent Systems Under Communication Delays and DoS Attacks

HDWM-based Consensus Control for Multi-agent Systems Under Communication Delays and DoS Attacks

Consensus Control for Multiagent Systems Under Asymmetric Actuator Saturations With Applications to Mobile Train Lifting Jack Systems

In this paper, the consensus control problem is investigated for mobile train lifting jack systems (TLJSs) of electric multiple units in the context of distributed industrial systems. First, a kind of global consensus controller is dedicatedly designed to deal with the underlying actuator limitation that is a typical phenomenon in mobile TLJSs and is referred to as actuator saturation. In order to better cater for the impact from the TLJSs, we consider the asymmetric actuator saturations (rather than their symmetric counterparts) whose side effects are later attenuated by means of a novel Lyapunov-function-based method. A series of experiments are conducted on mobile TLJSs so as to illustrate the effectiveness of the proposed consensus control algorithm.

Fixed-Time Prescribed Performance Consensus Control for Multiagent Systems With Nonaffine Faults

This paper studies the fixed-time consensus tracking control of nonlinear multi-agent systems (NNMASs) suffering from non-affine faults. A fixed-time command filter is constructed to solve the “explosion of complexity” issue, and a novel fixed-time error compensation mechanism is designed to eliminate filtering errors. The adaptive fuzzy control technique is introduced to deal with the unknown nonlinear terms containing non-affine fault functions. A new fixed-time fault-tolerant control scheme based on the modified prescribed performance technology is proposed for the NNMASs, which ensures that the closed-loop system satisfies the practical fixed-time stability. In addition, the consensus tracking errors of the NNMASs converge to a given range within a prescribed performance bound in a fixed time. Finally, comparative simulation results show the effectiveness of the proposed method.

Finite Time Fully Distributed Consensus Control for Multi-agent System With Input Saturation and Limited Communication Resources

Finite Time Fully Distributed Consensus Control for Multi-agent System With Input Saturation and Limited Communication Resources

Event-triggered boundary consensus control for multi-agent systems of fractional reaction–diffusion PDEs

The distributed consensus is considered for multi-agent systems (MASs), which characterized by fractional reaction–diffusion partial differential equations (RDPDEs) in this paper. Based on Lyapunov technique and linear matrix inequalities (LMIs) theory, the consensus can be realized via two novel event-triggered boundary control schemes. Firstly, a novel convergence principle subject to finite time is presented for the continuously differentiable function. Secondly, the cooling fin on surface of high-speed aerospace vehicle is remodeled by fractional RDPDEs system, and the well-posedness of presented system is discussed applying the monotone iterative approach. Thirdly, according to the presented static event-triggered boundary control strategy, the consensus criterion in finite time is addressed in the form of LMIs, in addition, the settling time is calculated accurately. Applying the dynamic event-triggered control protocol, the Mittag-Leffler (M-L) consensus condition is achieved. Moreover, the Zeno behaviors are ruled out for proposed event-triggered mechanisms. Finally, the high-speed aerospace vehicle model is presented to verify the effectiveness of the control performance.

Fully distributed prescribed-time consensus control of multiagent systems under fixed and switching topologies

In this paper, the fully distributed prescribed-time control methods for the consensus problem of networked multiagent systems are studied for the first time, considering both fixed and switching topologies. Unlike existing results of prescribed-time consensus, the proposed approaches eliminate the need for global topology information, while achieving the consensus in a prescribed time that is irrelevant to the initial conditions. First, for the leaderless consensus problem, the prescribed-time adaptive control protocols under fixed and switching topologies are proposed to achieve consensus, respectively. Then, we extend our investigation to the leader-following consensus and the prescribed-time adaptive control protocols under fixed and switching topologies are respectively devised to ensure that the followers' states reach an agreement with the leader's states being the consensus values. Theoretical analysis proves the prescribed-time convergence of control errors and the boundedness of the control inputs. Finally, simulation examples are provided to illustrate the effectiveness of the proposed fully distributed control approaches.

Observer‐based adaptive event‐triggered consensus for linear multiagent systems with bounded leader's input under directed graphs

AbstractThe consensus problem of linear multiagent systems (MASs) with a leader of bounded input under directed graphs is an important research topic. However, for the directed graphs, the existing methods dealing with consensus problem rely on the global information or continuous communication among neighbors. This paper focuses on the consensus problem of linear MASs with a leader of bounded input by adaptive event‐triggered output feedback control, where the digraph contains a spanning tree with the leader as the root. A fully distributed event‐triggered consensus protocol is presented by several observers, which are used to estimate the upper bound of the leader's input and the state of each agent, respectively. Compared with the existing results on the consensus control of MASs under directed graphs, the proposed method is independent of any global information, and is suitable for situations where the states of all agents is unavailable and only a part of followers know the upper bound of the leader's input.