Event-triggered Communication Research Articles

Resilient Event-Triggered Load Frequency Control for Cyber-Physical Power Systems Under DoS Attacks

In cyber-physical power systems (CPPSs), additional control as the compensating control plays a very important part in load frequency control (LFC) systems. The additional control in the LFC system is constrained by limited communication resources and cyber-attacks, which may cause performance degradation or destabilize the system. Accordingly, this paper proposes resilient event-triggered LFC for CPPSs with an additional control loop under denial-of-service (DoS) attacks. Firstly, a resilient event-triggered communication scheme is presented to reduce the occupation of communication resources under DoS attacks in the additional control loop. Then, different from existing event-triggered LFC systems, this paper establishes a novel switched LFC system model, where the resilient event generator is integrated into an additional control loop when suffering from DoS attacks. It is the first time that the additional control loop of the LFC system simultaneously considers communication resources and cyber-security. Furthermore, we derive exponential stabilization criteria by applying the Lyapunov stability theory based on the established model. Criteria are derived to obtain the weighting matrix and controller gain simultaneously by applying the linear matrix inequality technique. Finally, a one-area and two multi-area CPPSs with the additional control loop under DoS attacks are used to testify the availability of the proposed resilient event-triggered LFC scheme.

Adaptive formation control of nonlinear multi-agent systems with dynamic event-triggered communication

Adaptive formation control of nonlinear multi-agent systems with dynamic event-triggered communication

Network-Induced Asynchronous Fuzzy Control for Vehicle Steering Using Switching Event-Triggered Communication Mechanism

Network-Induced Asynchronous Fuzzy Control for Vehicle Steering Using Switching Event-Triggered Communication Mechanism

Distributed Formation Control for a Multirobotic Fish System With Model-Based Event-Triggered Communication Mechanism

This paper confronts the formation control problem for a multi-robotic fish system with event-triggered communication mechanism. A three-dimensional (3-D) distributed formation control framework is proposed to drive the robotic fish agents to an anticipated configuration aligning with a moving target. In particular, a consensus-based formation control law is intended to realize the two-stage formation control process. Taking the energy-constrained occasions into consideration, the communication structure and event-triggered protocols are initially tailored. Meanwhile, the Lyapunov function is employed and the globally asymptotic stability of the proposed method is fully demonstrated. Afterwards, making use of the local measurements of triggering times, the unscented Kalman filter (UKF) is introduced and a novel model-based event-triggered mechanism is put forward to further mitigate otiose communication consumption. Finally, adequate simulations and experiments are carried out to verify the effectiveness and robustness of the proposed scheme. Thereby, the proposed formation control frame offers great potential for future practical marine operations of the underwater multi-agent systems.

Event-triggered distributed Nash equilibrium seeking over directed graphs and its application to power management

In this paper, the problem of distributed discrete-time Nash equilibrium computation with event-triggered communication over directed graphs is studied. Each agent can only receive strategies from its neighbors through a directed and unbalanced graph, while its cost function may rely on the information of all agents. To this end, each agent needs to estimate the strategy profile. Meanwhile, an event-triggered communication mechanism is introduced, which can effectively compensate for network resource loss. Concretely, specific moments that each agent transmits its information are decided by the pre-designed event-triggered condition. In this setting, two discrete-time Nash equilibrium seeking algorithms with event-triggered communication are designed, respectively considering that the Perron-Frobenius eigenvector of the adjacency matrix associated the directed communication graph is known and unknown in advance. It is rigorously proved that both algorithms can linearly converge to the Nash equilibrium with a small error. Finally, a power management example in smart grids is presented to verify the performance of proposed algorithms.

A distributed event-triggered algorithm for constrained economic dispatch problem via virtual communication

A new distributed discrete-time event-triggered optimization algorithm is proposed based on the Newton–Raphson iterative method and the consensus algorithm in this paper. With the aid of virtual communication strategy, the proposed algorithm can solve economic dispatch problem with power output constraints under undirected and connected network. Moreover, the waste of network resources can be reduced by adopting event-triggered communication strategy. In addition, the linear convergence of the algorithm is strictly proved by the discrete Lyapunov stability theory. Finally, three numerical simulation examples are given to show the effectiveness and advantages of the proposed algorithm.

Distributed Coordination Control of Networked Lagrangian Systems With Velocity and Input Constraints Over Event-Triggered Communication

In this paper, the coordination control problem of networked Euler-Lagrange (E-L) systems with velocity and input constraints over event-triggered communication is considered. A novel distributed controller is proposed to achieve the control objective under reasonable initial conditions. Unlike existing methods, neither the proposed controller nor the event-triggered scheme relies on any global information of the communication graph. Also, Zeno behavior is proved to be non-existent. In addition, the constraints on the system velocity and input will not be violated. Finally, case studies and experiment results are provided to show the effectiveness of the proposed method.

Multiagent System With Periodic and Event-Triggered Communications for Solving Distributed Resource Allocation Problem

This article mainly investigates how to reduce the communication cost in multiagent system (MAS) for distributed optimization. First, a continuous-time distributed optimization model based on MAS is proposed for resource allocation (RA) with periodic communication. All agents in the system do not need to be in constant contact with their neighbors, but contact at set intervals. This will greatly reduce the communication consumption of the system. Second, to further reduce the communication cost, MAS with event-triggered communication is proposed based on periodic communication. It is proved that the system is convergent to an optimal solution of the investigated problem subject to bound and equality constraints. Finally, two examples with simulations are given to verify the performance of the proposed system.

Channel-Level Event-Triggered Communication Scheme for Path Tracking Control of Autonomous Ground Vehicles With Distributed Sensors

In this paper, a channel-level event-triggered communication scheme is investigated for path tracking control of autonomous ground vehicles via an in-vehicle network to ensure path tracking performance while reducing network resource utilization. First, a path tracking system is established considering the effect of norm bounded uncertainty on lateral vehicle dynamics, and a state feedback path tracking controller is designed within the Takagi–Sugeno fuzzy framework. Next, a decentralized event-triggered communication scheme is adopted between the sensors and controller, which makes it possible to save communication resources at the channel level. Finally, the results in the CarSim-Simulink joint-simulation environment show that the proposed controller can ensure a reliable path tracking performance in both lateral offset and heading error. At the same time, compared with the simple time-triggered scheme, the proposed method can effectively reduce the usage of communication resources by more than 80%.

Event-Triggered Distributed State Estimation: A Conditional Expectation Method

This paper mainly focuses on distributed filtering for a discrete time-varying system observed by a sensor network, where each sensor can measure some partial state information of the system and communicate with its neighbours. A novel distributed event-triggered communication mechanism is designed to reduce the communication rate among the sensors and guarantee the performance of the filter. With a data scheduler, the sensor is able to decide whether to transmit data to its neighbours. By applying Gaussian approximation, an evaluation of the effect caused by the non-transmission event is derived, which characterizes the tradeoff between communication rate and state estimation performance. Subsequently, a corresponding sub-optimal filtering gain design protocol is proposed. Compared with the literature, the filtering algorithm proposed in this paper is less conservative. Finally, numerical simulation is provided to illustrate the improvement of performance and the robustness of the approximation.

Predefined-Time Distributed Nash Equilibrium Seeking for Noncooperative Games With Event-Triggered Communication

In this paper, we investigate a predefined-time distributed Nash equilibrium seeking problem for a class of noncooperative games under an event-triggered scenario. To achieve fast convergence while reducing the communication and computation costs, a novel distributed Nash equilibrium seeking approach is proposed by applying the gradient play, a consensus-based estimator, and a time base generator (TBG). Different from existing works on Nash equilibrium computation under a bounded convergence time, the design of distributed algorithm in this paper is based on a newly developed TBG. The new TBG is more efficient and convenient than the traditional TBG. By virtue of an adaptive event-triggered rule, the distributed estimators are designed to estimate other players’ actions over strongly connected directed graphs. Moreover, the predefined-time convergence analysis of the players’ actions to the Nash equilibrium is given based on the Lyapunov stability method. Finally, simulation studies are provided to demonstrate the effectiveness of the constructed TBG and the advantages of the derived strategy.

Distributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation

Distributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation

Distributed Event-Triggered Secondary Control of Microgrids With Quantization Communication

Taken communication networks with limited resources in practical microgrids into consideration, a communication scheme, combined with an event-triggered communication scheme and quantization technology, is designed in the distributed optimal secondary control for islanded AC microgrids to reduce communication loads. In addition, switching communication networks are considered in microgrids to enhance the flexibility and the extendibility. In comparison with the existing distributed secondary control methods, the proposed distributed control strategy based on the designed communication scheme not only achieves the frequency and voltage restoration and the optimal active power sharing, but also reduces both the communication frequency and the amount of transmitted data in networks. Moreover, the presented communication scheme can exclude the Zeno behavior. Simulation results are given to evaluate the effectiveness of the proposed method.

Fully Distributed Control of Multiagent Networks With Edge-Based Event-Triggered Communication

This paper addresses the synchronization problem of linear multi-agent systems with intermittent communication. To solve this problem, we propose an adaptive distributed control algorithm with edge-based event-triggering mechanisms that differs fundamentally from existing approaches in that it does not employ any form of global topology information and absolute state information. Instead, agents update their control signals and check triggering conditions based on relative state information. As our main contribution, we prove that all agents achieve global asymptotic synchronization with strictly positive minimum inter-event times by using the proposed event-triggered control method when the communication graph is connected. The main result is illustrated with an example, and through which we demonstrate the effectiveness of the proposed algorithm.

Dynamic Event-Triggered Consensus for Linear Multi-Agent Systems With Hybrid Intelligence

In this brief, consensus control is investigated for general linear multi-agent systems (MASs) over undirected communication topologies. Considering that the agents in MASs may have nonidentical intelligence characteristics, the concept of intelligent level is introduced to characterize the intelligence characteristics of agents. A novel dynamic event-triggered communication mechanism is developed based on periodic sampled data and the intelligent levels of agents, in which the threshold parameter of the event-triggered condition updates periodically in accordance with a prescribed dynamic law. By making use of a delayed system method and Lyapunov stability theory, some sufficient conditions are derived to guarantee the desired consensus under a novel delicately designed control protocol. Finally, the effectiveness of the proposed approach is validated by a simulation example.

Force-reflecting event-triggered predefined-time cooperative control for teleoperation of NMMs via data-driven based observer

This paper investigates the cooperative control problem for the teleoperation system of networked mobile manipulators (NMMs), in which each mobile manipulator is subject to nonholonomic constraints, model uncertainty and external disturbances. The control objective of such a teleoperation system is to synchronize the task-space position between the human-controlled master manipulator and the slave mobile manipulators, and meanwhile enable the slave mobile manipulators to achieve a formation. For this purpose, a hierarchical predefined-time cooperative control (HPTCC) framework involving predefined-time distributed event-triggered (PTDET) estimator, predefined-time stability (PTS) controller and data-driven based (DDB) observer, is proposed. The PTDET estimator is used to generate the information that the slave mobile manipulators need to track and enable multiple slave mobile manipulators to interact through an event-triggered communication network. The PTS controller is presented to ensure the predefined-time stability of the master manipulator and the slave ones. Moreover, for improving the telepresence of the considered teleoperation system, the DDB observer is proposed to reestablish the interaction force between the slave mobile manipulators and the complex operating environment (i.e., the environmental force) on the human operator side. Based on the hierarchical control analysis as well as Lyapunov theory, several sufficient conditions are derived to guarantee the predefined-time stability for the teleoperation system of NMMs. Finally, several simulations are conducted to demonstrate the effectiveness of the proposed control scheme.

Leader–follower sliding mode formation control of fractional-order multi-agent systems: A dynamic event-triggered mechanism

This paper examines the concept of the leader–follower formation for fractional-order multi-agent systems (FO-MASs) by utilizing dynamic event-triggered sliding mode control (SMC) method. Firstly, a dynamic event-triggered mechanism (DETM) is designed relying on the combined measurement vector, in which an auxiliary variable is introduced to dynamically adjust the threshold for each fractional-order agent system. Unlike most existing event-triggered communication mechanisms, whose threshold parameters are always fixed, the threshold parameters in our designed event-triggered conditions can be dynamically adjusted according to the fractional-order dynamic rule. Numerical results show that the proposed DETM can achieve a better system performance in reducing the sampling frequency and the expected formation performance. Secondly, the leader–follower formation control problem is transformed into checking the asymptotic stability problem of the closed-loop system. In addition, due to the memorability of fractional calculus operators, a distinctive condition is established to avoid the occurrence of Zeno behaviors reported in existing dynamic event-triggered schemes. Finally, a simulation example is presented to illustrate the effectiveness and feasibility of the dynamic event-triggered SMC method proposed in this paper.

Adaptive full-order sliding mode bounded attitude control for spacecraft formation flying with event-triggered communication

This paper provides an event-triggered finite-time adaptive bounded controller for attitude tracking of spacecraft formation flying under external disturbances and limited communication. To facilitate the realization of bounded control, a novel full-order terminal sliding mode surface is established according to the hyperbolic tangent function. To reduce the communication frequency among formation members, an event-triggered control strategy that can converge to zero in finite time is investigated based on the full-order sliding mode surface. Under the proposed control strategy, the spacecraft only send their information to neighboring spacecraft when the trigger error exceeds the defined threshold. Rigorous theoretical analysis provides that finite-time convergence and Zeno-free are achieved under the proposed controller. Finally, numerical simulations are exhibited to illustrate the effectiveness of the proposed control law.

Distributed event-triggered unadjusted Langevin algorithm for Bayesian learning

This paper presents a distributed event-triggered unadjusted Langevin algorithm (DETULA) to address the Bayesian learning problem. We consider a set of networked learning agents who have access to their own independently distributed data sets. The objective of each agent is to reconstruct the global posterior of the unknown model parameters through local learning along with interaction with neighboring agents. We propose an event-triggered communication mechanism for a distributed Langevin algorithm to limit the inter-agent interactions and thus reduce the communication overhead. We provide conditions on the algorithm step sizes and the triggering threshold to ensure mean-square consensus of the agents’ parameter estimates and convergence of the estimates to the global posterior as if the data sets were aggregated at a central location. A major improvement of our result over previous studies is the establishment of said consensus without imposing any bounded restriction of the gradient of the objective function. Additionally, we establish probabilistic guarantees to prevent consecutive triggering by any agent while maintaining the same rate of convergence as in the case without event-triggering We demonstrate the DETULA using distributed supervised-learning problems. Our results indicate that the agents successfully recover the global posterior by periodically sharing their samples with neighbors.

Distributed Fixed-Time Secondary Control for MTDC Systems Using Event-Triggered Communication Scheme

Multi-terminal DC transmission (MTDC) systems have attracted much attention due to their significant advantages in long-distance and high-capacity transmission. To improve their reliability and operation performance, a distributed fixed-time secondary control of frequency restoration and active power sharing is proposed under event-triggered communication, which only depends on the states of each AC grid and its neighbors. By utilizing Lyapunov theory, we prove that the MTDC system with the fixed-time secondary control can be stable in a settling time, and the conditions of the settling time are established for fixed-time algorithms. In addition, we simulate a five-terminal MTDC system in Matlab/Simulink. Several cases of MTDC systems are exhibited to showcase how well the suggested controller works when dealing with load changes and attacks. The comparison of the number of event-triggered instants shows that the proposed control method can effectively reduce communication resources.