Event-triggered Consensus Control Research Articles

Adaptive neural network dynamic event-triggered consensus control for nonlinear multi-agent systems subject to sensor deception attacks and actuator faults

Adaptive neural network dynamic event-triggered consensus control for nonlinear multi-agent systems subject to sensor deception attacks and actuator faults

Distributed adaptive event-triggered consensus control for high-order multi-agent systems

In this paper, a distributed adaptive event-triggered control approach is proposed for the consensus problem of high-order multi-agent systems (MASs) with unknown dynamics and external disturbances. First, to save communication resources, the event-triggered control is proposed to ensure the consensus of MASs, where the trigger condition is established based on the neighbors’ information. The approximation properties of neural networks are used to address the unknown dynamics and external disturbances. Second, rigorous theoretical analysis proves that the MASs can achieve the leader-following consensus, as long as the communication graph of MASs contains a spanning tree with the leader as the root node. The filtered tracking errors and adaptive parameters estimated errors are proved to be uniformly ultimately bounded without Zeno behavior. Finally, the simulations and experiments illustrate the feasibility and effectiveness of the theoretical results.

Distributed Dynamic Event-Triggered Consensus Protocol for General Linear Multiagent Systems Without Accurate System Information.

This study focuses on distributed event-triggered consensus control under the scenario where only inaccurate agent model information is available. By designing a novel triggering error, a distributed dynamic event-triggered consensus (DETC) protocol is proposed for multiagent systems (MASs) with general linear dynamics over digraphs, without accurate a priori information of agent models. To improve the efficiency of the dynamic triggering law, a mixed triggering threshold is designed with a resilient function integrated to further enlarge interevent intervals. Within the proposed DETC protocol, the computational cost is significantly reduced especially for MASs with nonsparse and high-dimensional agent system matrices. In addition, for each individual agent, the states of neighboring agents used for triggering detections or controller updates are required in an on-demand (instead of continuous) way, which preserves communication resources and facilitates practical implementation. The feasibility of the designed DETC protocol is corroborated by rigorous theoretical analysis on consensus convergence and Zeno behavior exclusion. Finally, simulations are shown to demonstrate the effectiveness of the studied theory.

Strong Non-Zeno Mixed Adaptive Dynamic Event-Triggered Control for Distributed Consensus.

This article studies the distributed adaptive event-triggered consensus control problem of linear multiagent systems. A strong non-Zeno mixed adaptive dynamic event-triggering scheme is proposed, which guarantees a strictly positive minimum interevent time (MIET) between any two consecutive events. A model-based event-triggered fully distributed adaptive control law is presented without using prior global information about the communication topology. Moreover, a hybrid system model is constructed to facilitate the stability analysis of the closed-loop system. It is shown that the proposed control strategy can achieve asymptotic consensus of all agents via intermittent communication in a fully distributed way, while guaranteeing the strictly positive MIET property. Finally, the effectiveness of the designed control method is illustrated by a simulation example.

Edge-based event-triggered consensus control of multi-agent systems against DoS attacks

This article focuses on the security consensus control for general linear multi-agent systems against denial of service (DoS) attacks. In particular, an edge-based event-triggered protocol is proposed to reduce unnecessary information transmission through energy-limited and fragile networks, where the dynamic event-triggered condition is designed by introducing internal dynamic variables. The state of agents is dynamically estimated, and the control inputs based on estimated value can offer better control performance. It is demonstrated that under DoS attacks, the security consensus of multi-agent systems can be realised without Zeno behaviour by adopting the dynamic edge-based event-triggered control strategy. Finally, a numerical simulation example is included to prove the effectiveness of the proposed method.

Hybrid Adaptive Event-Triggered Consensus Control with Intermittent Communication and Control Updating

Hybrid Adaptive Event-Triggered Consensus Control with Intermittent Communication and Control Updating

Novel Dynamic Event-Triggered Consensus Control of Multiagent Systems With Markovian Switching Topologies Under DoS Attacks.

This article focuses on the issue of novel dynamic event-triggered consensus control of multiagent systems (MASs) with denial-of-service (DoS) attacks. Different from the conventional Markovian switching topologies, the generally uncertain semi-Markovian (GUSM) switching topologies with partially unknown elements and time-dependent uncertainties are constructed for the leader-following MASs by considering the equipment performance and external uncertain environment influence. To save communication resources, the novel dynamic memory event-triggered strategy (DMETS) is presented to decrease the frequency of communication between agents. Some secure consensus control criteria are established for the MASs with GUSM switching topologies and DoS attacks due to the potential system communication disruption caused by attackers. Finally, two physical system examples are designed to prove the effectiveness of the presented method.

Fast Finite-Time Observer-Based Event-Triggered Consensus Control for Uncertain Nonlinear Multiagent Systems with Full-State Constraints.

This article studies a class of uncertain nonlinear multiagent systems (MASs) with state restrictions. RBFNNs, or radial basis function neural networks, are utilized to estimate the uncertainty of the system. To approximate the unknown states and disturbances, the state observer and disturbance observer are proposed to resolve those issues. Moreover, a fast finite-time consensus control technique is suggested in order to accomplish fast finite-time stability without going against the full-state requirements. It is demonstrated that every signal could be stable and boundless, and an event-triggered controller is considered for the saving of resources. Ultimately, the simulated example demonstrates the validity of the developed approach.

Adaptive neural event-triggered consensus control for unknown nonlinear second-order delayed multi-agent systems

In this paper, we discuss event-triggered consensus control for a heterogeneous second-order multi-agent systems with unknown nonlinear functions and state delays (SODMASs). Firstly, a broad adaptive dynamic event-triggered mechanism (ETM), which includes many existing ETM, is proposed. Based on this ETM and the approximation property of neural networks, an adaptive event-triggered protocol with weight estimation of neural network and time-varying integral gain compensation is designed to reduce communication frequency and to eliminate the uncertainty of nonlinear function and state delays. Then, the consensus problem for the heterogeneous SODMASs under the protocol is solved successfully by selecting a suitable Lyapunov–Krasovskii functional. In addition to these, it is also proved that all agents can exclude Zeno behavior under the proposed event-triggered protocol. Finally, a numerical example is given to verify the effectiveness of the proposed consensus protocol algorithm.

Fuzzy Fixed-Time Event-Triggered Consensus Control for Uncertain Nonlinear Multiagent Systems With Memory-Based Learning

Fuzzy Fixed-Time Event-Triggered Consensus Control for Uncertain Nonlinear Multiagent Systems With Memory-Based Learning

Event-triggered consensus tracking control of flexible manipulators with nonlinear time-varying fault-tolerant actuators and input constraint

This paper introduces a novel event-triggered consensus control strategy for a multi-agent system composed of underactuated flexible manipulators. Most existing research on consensus tracking control assumes that the model targeted is fully actuated, the control signal is continuous, and that both time-varying actuator failures and input constraints are managed separately. These challenges were tackled in this study within the context of multi-agent systems, addressing input constraints and nonlinear time-varying actuator failures simultaneously. Moreover, an event-triggered mechanism is proposed to reduce signal communication. A double closed-loop consensus tracking method is designed based on the multi-agent topology, enabling all flexible manipulators to track the angle and angular velocity of the leader and an adaptive control law is designed to solve actuator faults. Finally, the simulation results demonstrate the effectiveness of the proposed control scheme.

Monolithic design of self-adaptive CMOS converter and robust event-triggered consensus control for integration of multi-renewable energy sources with battery storage system

Recently, integrating renewable energy sources (RESs) has been one of the most effective ways to overcome the power shortage problems due to the cumulative load demand, which cannot be covered using conventional power production. DC-DC converters with a wide voltage conversion range are highly important when integrating RESs to achieve voltage matching. In recent years, many large-scale improvements have been made to the DC-DC converters to improve reliability, effectiveness, flexibility, modularity, and cost-effectiveness. This study investigates the feasibility of integrating RESs and designing the most effective structure using complementary metal-oxide semiconductors (CMOS) for DC-DC converters. A novel monolithic CMOS buck converter with an adaptive sensing feedback system (ASFS) circuit is proposed for renewable integrated systems. The proposed converter based on ASFS provides a wide range of conversion voltages, low cost, and reliability. It depends on the pulse-width modulation (PWM) technique with a voltage-control duty-cycle (VCDC) circuit. The proposed multi-input DC-DC converter is tested to integrate three RESs to form an integrated hybrid system. The proposed converter is built to integrate the PV, wind turbine (WT), wave energy source, and battery energy storage system (BESS). The proposed DC-DC converter is tested to adjust the output voltage of the RESs at 12 V with a load current of 2.4 A to facilitate the integration process. The results show the success of the proposed converter in maintaining the output voltage at 12 V, with maximum efficiency of the CMOS buck DC-DC converter reaching 96.25 % over a wide input voltage range from 15 V to 35 V. Moreover, the maximum peak-peak ripple over the output voltage reaches 600 mV at the maximum input voltage of 35 V. A control method-based event-triggered consensus algorithm has been proposed to regulate the system voltage and ensure active power sharing in the microgrid system. The controller's settling time and rise time have been measured, and a robustness analysis has been performed based on the connections and disconnections of DGs and the impact of faults.

Event-Triggered Consensus Control in Euler–Lagrange Systems Subject to Communication Delays and Intermittent Information Exchange

In this paper, we investigate the consensus control problem of Euler–Lagrange systems which can be used to describe the motion of various mechanical systems such as manipulators and quadcopters. We focus on consensus control strategies, which are important for achieving coordinated behavior in multi-agent systems. The paper considers the key challenges posed by random communication delays and packet losses that are increasingly common in networked control systems. In addition, it is assumed that each system receives information from neighboring agents intermittently. Addressing these challenges is critical to ensure the reliability and efficiency of such systems in real-world applications. Communication delay is time-varying and can be very large, but should be smaller than some bounded constant. To decrease the frequency of control input updates, we implement an event-triggered scheme that regulates the controller’s updates for each agent. Specifically, it does not update control inputs at traditional fixed intervals, but responds to predefined conditions and introduces a dynamic consensus item to handle information irregularities caused by communication delays and intermittent information exchange. The consensus can be achieved if the communication graph of agents contains a spanning tree with the desired velocity as the root node. That is, all Euler–Lagrange systems need to obtain the desired velocity, directly or indirectly (via neighbors), to reach consensus. We establish that the Zeno behavior can be avoided, ensuring a positive minimum duration between successive event-triggered instances. Finally, we provide simulation results to show the performance of our proposed algorithm.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems with a Designable Minimum Inter-Event Time

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems with a Designable Minimum Inter-Event Time

Event-Triggered Consensus Control for Nonlinear Singular Multi-Agent Systems under Directed Topology

Event-Triggered Consensus Control for Nonlinear Singular Multi-Agent Systems under Directed Topology

Event-triggered consensus control of linear multi-agent systems under intermittent communication

This paper proposes a novel state-based intermittent communication mechanism to study the event-triggered consensus problem of linear multi-agent systems. The main feature of this mechanism is that whether the agents execute the control protocols is based on the current error state. In this communication mechanism, two frontier lines namely safety frontier and intermittence frontier are constructed to monitor the error state. On basis of this, a novel intermittent rule is proposed to arrange the work time and the rest time online with respect to the error state in real time. Then by utilizing state estimates of neighboring agents, a distributed event-triggered protocol is integrated into intermittent communication, under which the overall consensus of multi-agent systems can be realized. It is interesting to see that the events are eliminated during the rest time and the amount of samplings can also be reduced. Compared to the current time-based mechanisms, the proposed state-based intermittent communication mechanism has more tolerant of rest time. At last, a numerical simulation with two cases is provided to verify our results.

Secure Fully Distributed Event-Triggered Consensus of Multi-Agent Systems Against Distributed Sequential Scaling Attacks

This article is concerned with the secure fully distributed event-triggered consensus problem of general linear multi-agent systems subject to distributed sequential scaling (DSS) attacks. First, a generic DSS attack model is proposed, which enables different attack strategies in terms of scaling factors, attack frequency and duration to be incorporated in various communication channels. Different from existing attack models, the DSS attack is a kind of scaling attacks in which attack sequences are characterized by the sequential attacks and with distributed attack strategies for different attack objectives. To resist the adverse effects of such DSS attacks and further reduce the unnecessary communication consumption of each communication channel, a channel-based dynamic event-triggered mechanism is next presented. Moreover, a fully distributed event-triggered consensus control protocol is developed such that the dependence of any global information of the network topology can be eliminated. Formal analysis criteria on the asymptotic convergence of the resultant consensus errors and Zeno-freeness are then derived, where the relationship of the triggering parameters, distributed scaling factors and attack constraints is explicitly expressed. Furthermore, an offline algorithm without any global information is provided to determine both the adaptive consensus protocol gain matrices and the triggering parameters. Therefore, the parameters calculated by this algorithm are applicable to multi-agent systems of different scales, which also confirms the flexibility and scalability of the proposed fully distributed event-triggered consensus control protocol. Finally, two simulation examples involving different scales of intelligent vehicles are given to validate the efficacy of the obtained theoretical results.

A Novel Adaptive Event-Triggered Consensus Control Approach to Multi-Agent Systems With Guaranteed Positive MIET

A Novel Adaptive Event-Triggered Consensus Control Approach to Multi-Agent Systems With Guaranteed Positive MIET

Distributed Dynamic Event-Triggered Consensus Control for Multiagent Systems With Guaranteed Performance and Positive Inter-Event Times

This paper addresses the distributed consensus issue of linear multiagent systems (MASs) subject to disturbances. First, a fully distributed adaptive control law is established for each agent, removing the assumption that global information should be known prior. Additionally, unlike existing consensus studies, the restrictions on continual communication among agents and constant controller updates are eliminated through the designed state observers and event-triggered conditions (ETCs). Moreover, an innovative event-triggered condition (ETC) is created that, via the inclusion of a dynamic parameter, captures mixed triggering and time-varying thresholds as special cases. Particularly, distinct from some dwell time methods that enforce inter-event time (IET) greater than zero at the expense of asymptotic stability, positive inter-event times (IETs) and asymptotic stability can be guaranteed simultaneously by the suggested event-triggered conditions (ETCs) in the absence of disturbances. Furthermore, positive minimum inter-event times (MIETs) can be maintained even in the presence of disturbances, which indicates the robustness of the proposed event-triggered mechanism (ETM). It is shown that the suggested technique performs disturbances suppression for all agents in a completely distributed manner while omitting Zeno behavior. Finally, a simulation example demonstrates the suggested scheme’s efficacy. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The multiagent consensus problem is considered in this paper, which can be applied to some practical systems, e.g., the unmanned aerial vehicles formation problems, as the control objective in these applications can be converted into the consensus problem of MASs. Different from existing results, a novel ETM is proposed, reducing agents’ communication and preventing continuous controller updates. In addition, disturbances widely exist in engineering. The proposed method ensures that the interval between two consecutive event triggers is greater than a small positive constant. Therefore, it is helpful for applying the proposed method in practical engineering. Finally, the established method is applied to a two-mass-spring control problem, and the effectiveness is illustrated. It is anticipated that the proposed approach can be extended to MASs with more realistic network-induced constraints and applied to more practical engineering systems.

Observer-Based Event-Triggered Consensus Control of Multi-Agent Systems With Time-Varying Communication Delays

Observer-Based Event-Triggered Consensus Control of Multi-Agent Systems With Time-Varying Communication Delays