Dynamic Event-triggered Strategy Research Articles

Event-triggered exponential stabilization of delayed systems on time scales

This paper addresses exponential stabilization issue for delayed systems on time scales. A dynamic event-triggered strategy (DETS) is proposed that relies on both the last sampled state and an exponential threshold, which can reduce the transmission frequency of the feedback control signal. Through inequality techniques and comparison method, a criterion of exponential stabilization for the underlying systems is presented. Besides, the measurement errors and estimation of system states are used to prevent Zeno behavior in DETS design. Two simulations are provided to illustrate the theoretical outcomes.

Dynamic event-triggered control for multi-channel cyber–physical systems under denial-of-service attacks

This paper studies the problem of dynamic event-triggered control in multi-channel cyber–physical systems subject to denial-of-service attacks, and the attacks are independent and asynchronous in different channels. A switching scheme is proposed to address the complexity of multi-channel network attacks, under which the sufficient conditions for closed-loop stability of the systems are obtained. Additionally, considering the different decay rates caused by the switching logic, an equivalent decay rates method, which reveals the relationship between the tolerable attack intensity and the dynamic event-triggering parameters, is proposed. Furthermore, it is demonstrated that the dynamic event-triggered strategy outperforms the traditional static approaches in terms of saving communication resources, which is also verified by a simulation example.

Robust H∞ consensus for uncertain linear multi-agent systems on directed topologies: A dynamic event-triggered strategy

Considering the asymmetry of the system matrix caused by directed communication networks, a dynamic event-triggered control protocol for the robust [Formula: see text] consensus of uncertain linear multi-agent systems accompanied by external disturbances on directed topologies is proposed. Through the introduction of the controlled output and generalized algebraic connectivity for directed graphs, the consensus problem is converted to the event-triggered stabilization of the uncertain linear closed-loop system with disturbance. On the basis of the relative state of neighbor agents at event-times and the introduced dynamic variables, a dynamic event-triggered control protocol is put forward, and the linear matrix inequality sufficient conditions for the system to achieve robust [Formula: see text] consensus are obtained after a rigorous proof. Then, linear matrix inequalities are further decoupled to greatly reduce the computational complexity, and the parameters of the control protocol are determined by solving the decoupled linear matrix inequalities. Finally, simulations are applied for the verification of conclusions.

Event-triggered interval type-2 fuzzy control of networked systems with extended dissipative under Markovian switching

In this technical note, the problem of the extended dissipative control for interval type-2 fuzzy model with nonlinear network systems in the event-triggered framework is investigated. A novel dynamic event-triggered strategy is developed to ascertain the instants of activation. It has the advantage of reducing data transmission and optimising the utilisation of communication resources. On the basis of the proposed mechanism, the stochastic Lyapunov function including internal dynamic variables is constructed. Based on this function, coupled with the inequality scaling technique and the application of Dynkin's formula, we derive a sufficient condition for the system's stochastic asymptotic stability and extended dissipativity. The design of the dynamic event-triggered extended dissipative controller becomes challenging because the new sufficient condition is nonlinear for some matrix variables. However, utilising the Projection Lemma and the co-design approach, such a controller can be developed based on the obtained analysis result. The methodology is demonstrated through a rigorous numerical simulation case study.

Distributed Dynamic Event-Triggered Control to Leader-Following Consensus of Nonlinear Multi-Agent Systems with Directed Graphs.

This paper investigates achieving leader-following consensus in a class of multi-agent systems with nonlinear dynamics. Initially, it introduces a dynamic event-triggered strategy designed to effectively alleviate the strain on the system's communication resources. Subsequently, a distributed control strategy is proposed and implemented in the nonlinear leader-follower system using the dynamic event-triggered mechanism, aiming to ensure synchronization across all nodes at an exponential convergence speed. Thirdly, the research shows that under the dynamic event-triggered strategy the minimum event interval of any two consecutive triggers guarantees the elimination of Zeno behavior. Lastly, the validity of the calculation results is verified by a simulation example.

Stabilizability of multi-agent systems under event-triggered controllers

In view of the problems of large consumption of communication and computing resources in the control process, this paper studies a fundamental property for a class of multi-agent systems under event-triggered strategy: the S-stabilizability of a group of multi-agent systems with general linear dynamics under weakly connected directed topology. The results indicate that the S-stabilizability can be described in some way that the stabilizability region and feedback gain can evaluate the performance of the protocol. Firstly, a new distributed event-triggered protocol is proposed. Under this protocol, a kind of hybrid static and dynamic event-triggered strategy are presented, respectively. In particular, by using Lyapunov stability theory and graph partition tool, it is proved that the proposed event-triggered control strategy can guarantee the closed-loop system achieve S-stabilizability effectively, if at least one vertex in each iSCC (independent strongly connected component) cell receives information from the leader, which reflects the ability of distributed control law. Further, we demonstrate that the stabilizability can be realized if the initial system matrix A is Hurwitz. Moreover, it is confirmed that the designed static event-triggered condition is a limit case of dynamic event condition and can guarantee Zeno-free behavior. Finally, the validity of the theoretical results is proved by numerical simulation.

Dynamic Threshold Finite-Time Prescribed Performance Control for Nonlinear Systems With Dead-Zone Output.

This article investigates the tracking control problem for nonlinear systems. An adaptive model is proposed to represent the dead-zone phenomenon and solve its control challenge with a Nussbaum function in conjunction. Drawing inspiration from the existing prescribed performance control schemes, a novel dynamic threshold scheme is developed that fuses a proposed continuous function with a finite-time performance function. A dynamic event-triggered strategy is applied to reduce the redundant transmission. The proposed time-varying threshold control strategy has fewer updates than the traditional fixed threshold and improves the efficiency of resource utilization. A command filter backstepping approach is employed to prevent the complexity explosion faced by the computation. The suggested control strategy ensures that all system signals are bounded. The validity of the simulation results has been verified.

Output-Feedback Adaptive Control of a Class of Uncertain Nonlinear Systems With Dynamic Event-Triggered Strategy

Output-Feedback Adaptive Control of a Class of Uncertain Nonlinear Systems With Dynamic Event-Triggered Strategy

Distributed fixed-time event-triggered containment control for nonlinear multiagent systems with actuator faults

This paper is concerned with distributed fixed-time containment control for nonlinear multiagent systems with actuator faults via static and dynamic event-triggered strategies. A distributed fixed-time static event-triggered fault-tolerant controller is developed by employing the sign function, which eliminates the requirement for continuous control signal updates. To address the chattering phenomenon caused by the sign function, a distributed saturation controller is presented to enhance the control performance. To further reduce energy consumption and frequency of controller updates, a dynamic event-triggered strategy with an auxiliary parameter is proposed for each agent to dynamically regulate its threshold. The control scheme guarantees that the containment control objective is achieved within the settling time, and does not exhibit Zeno behavior. The effectiveness of the proposed control scheme is illustrated by simulation results.

Fuzzy Dynamic Event-Triggered Tracking Control for Semilinear Time-Delay Parabolic Systems

In this article, the fuzzy dynamic event-triggered tracking control problem of semilinear parabolic systems (SLPSs) with time-varying delay is investigated. Firstly, T-S fuzzy partial differential equation (PDE) models are introduced to describe the SLPSs. Secondly, a less conservative and more general fuzzy dynamic event-triggered strategy (DETS) is proposed to reduce communication consumption and avoid unnecessary continuous signal monitoring. Since the dynamic threshold is closely related to the currently sampled signal and the latest successfully transmitted signal, it can be promptly dynamically adjusted. In addition, on the basis of a reasonable assumption, a novel linear matrix inequality (LMI) relax technique is introduced to deal with the mismatched premise variables between the fuzzy systems and the fuzzy controller. By constructing the appropriate Lyapunov-Krasovskii candidate functional (LKCF), the criteria that the SLPSs can asymptotically track the target systems is derived, and the desired dynamic event-triggered control (DETC) gains can be obtained by solving a set of LMIs. The DETS reduces effectively communication resource consumption. Finally, the control problem of temperature distribution of catalytic rod in practical engineering application is given to verify the effectiveness and superiority of the proposed control scheme.

Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy.

This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly, the proposed one-to-all DET strategy is extended to a one-to-one DET strategy, where each agent transmits its state asynchronously to its neighbors. Furthermore, it is proven that the proposed two types of DET strategies do not have Zeno behavior. Finally, numerical simulations are provided to validate and illustrate the effectiveness of the theoretical results.

Event-triggered secure control of nonlinear multi-agent systems under sensor attacks

In this paper, a security consistent tracking control scheme with event-triggered strategy and sensor attacks is developed for a class of nonlinear multi-agent systems. For the sensor attacks on the system, a security measurement preselector and a state observer are introduced to combat the impact of the attacks and achieve secure state estimation. In addition, command filtering technology is introduced to overcome the “complexity explosion” caused by the use of the backstepping approach. Subsequently, a new dynamic event-triggered strategy is proposed, in which the triggering conditions are no longer constants but can be adjusted in real time according to the adaptive variables, so that the designed event-triggered mechanism has stronger online update ability. The measurement states are only transmitted through the network based on event-triggered conditions. The proposed adaptive backstepping algorithm not only ensures the security of the system under sensor attacks but also saves network resources and ensures the consistent tracking performance of multi-agent systems. The boundedness of all closed-loop signals is proved by Lyapunov stability analysis. Simulation examples show the effectiveness of the control scheme.

Asynchronous Control of Fuzzy Singularly Perturbed System With a Dynamic Event-Triggered Strategy

This paper is mainly concerned with the asynchronous control problem of fuzzy singularly perturbed systems (FSPSs) by designing an effective dynamic event-triggered control (ETC) strategy. Different from the existing results, a sample-based dynamic eventtriggering condition related to the singular perturbation parameter (SPP) " is proposed. Particularly, an auxiliary variable is employed in the eventtriggered mechanism (ETM), which changes with the fluctuation of the system state. By constructing a novel parameter-dependent Lyapunov functional, some sufficient conditions are derived to stabilize FSPSs and solve the "-dependent control gain. Furthermore, the upper bound of SPP _" related with the proposed control gain is determined. The Zeno behavior can be naturally avoided by applying the sample-based dynamic ETC. Finally, two examples including a nonlinear circuit are presented to validate the effectiveness of obtained results.

Event-based fault estimation and compensation for discrete-time systems via zonotopes

A fault estimation and compensation approach is presented for discrete-time systems with event-triggered scheme based on zonotope techniques in this paper. Instead of energy-bounded uncertainties, the dynamic system is supposed to be subjected to unknown but amplitude-bounded disturbance and noise, which is more in line with engineering practice. By introducing dynamic interval variables, a component-wise dynamic event-triggered strategy is utilized to reduce the consumption of communication resources. With considering the amplitude-bounded uncertainties and event-triggered scheme, a joint state-fault estimator is constructed to estimate the system state as well as possible system faults simultaneously, which are utilized to construct the fault-tolerant controller by compensating the effects of system faults. A co-design approach of the estimator, compensator, and event-triggered strategy is proposed to guarantee the stability and l1 performance of the system, based on which a zonotope-based interval estimation algorithm of system state and possible faults is provided to obtain the tight estimation of system state and faults. Eventually, simulation results on aircraft engine systems indicate that the designed method achieves a satisfactory fault estimation and fault tolerance performance, and also reduce the consumption of communication resources significantly.

Dynamic event-triggering sliding mode resilient control for multi-agent systems

The consensus problem for a multi-agent system (MAS) is investigated in this paper via a sliding mode control mechanism subject to stochastic DoS attack, which may occur on each transmission channel independently and randomly according to the Bernoulli distribution. A distributed dynamic event-triggered strategy is implemented on the communication path among agents, where dynamic parameters are introduced to adjust the threshold of event-triggered condition. After that, a distributed sliding mode controller is proposed for ensuring the stochastic consensus of the MAS. Meantime, a minimization problem is solved to obtain the correct controller gain matrix. At last, a numerical example is shown to demonstrate the presented results.

Simultaneous Fault Detection and Leader-Following Consensus for Multiagent Systems With Directed Graphs via Dynamic Event-Triggered Strategy

Simultaneous Fault Detection and Leader-Following Consensus for Multiagent Systems With Directed Graphs via Dynamic Event-Triggered Strategy

Dynamic Event-Triggered Approach for Distributed State and Parameter Estimation Over Networks Subjected to Deception Attacks

This study is focused on addressing the dynamic event-triggered distributed state and unknown parameter esti- mation problem for discrete-time nonlinear systems that have known linear dynamics and unknown nonlinearities and are subject to deception attacks. A neural-network-based unified estimation framework is introduced to estimate the unknown nonlinear function in conjunction with the system state and unknown parameters. Each sensor uses its own measurements and data from the neighboring sensors to calculate the overall estimates. The information-sharing network is assumed to be vulnerable to deception attacks, which are modeled using a Bernoulli distributed random variable. Additionally, a dynamic event-triggered strategy is adopted to alleviate resource consump- tion. Based on Lyapunov theory, the stability of the unified estimation framework is proven in terms of the uniformly ultimately bounded error. Moreover, the design conditions for the estimator are presented in the form of matrix inequalities. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed framework.

Observer-Based Secure Event-Triggered Bipartite Consensus Control of Linear Multiagent Systems Subject to Denial-of-Service Attacks

This brief deals with the secure bipartite consensus problem for linear multi-agent systems (MASs) with Denial-of-Service (DoS) attacks subject to an observer-based dynamic event-triggered strategy (OBDES). Two event-triggered strategies involved with dynamic threshold are developed in controller and observer channels. Based on the connected structurally balanced signed graph, a new observer-based secure control protocol integrated of OBDES and relative output measurements of neighboring agents is proposed. The control strategy with dynamic coupling gains is fully distributed, which only requires to obtain the observer information from neighboring agents. Then, some criteria for secure bipartite consensus under DoS attacks are established. In addition, it is demonstrated that the Zeno behavior cannot not occur. At last, a numerical simulation is provided to verify the effectiveness of the proposed controller.

Sliding mode control for 2D FMII systems: A bidirectional dynamic event-triggered strategy

This work is concerned with the event-triggered sliding mode control (SMC) problem for 2D FMII systems. Firstly, the partially ordered sequence is defined, and then, a bidirectional dynamic event-triggered mechanism is introduced into the S/C channel to reduce the unnecessary transmission. The evolutionary directions of both the triggered sequences and dynamic variables are consistent with the evolution direction of 2D FMII system states. Afterwards, the event-triggered SMC scheme is designed by introducing a model transformation. Also, sufficient conditions are established for guaranteeing both the reachability of the specified sliding surface and the exponential stability of the sliding mode dynamics on this sliding surface. Finally, the proposed control scheme is demonstrated via simulation results.

Distributed Finite-Time Consensus Control of Multiagent Systems With Fully Intermittent Communication via Dynamic Event-Triggered Strategy

Taking into account the multi-agent systems (MASs) with the single-order integrator dynamics and the directed internal topology, this brief is devoted to investigating the finite-time consensus (FTC) control problem based on the event-triggered strategy (ETS). A novel dynamic and state-dependent ETS is designed by using an adaptive and dynamic variable for each agent. Based on the triggered states, a discontinuous FTC control strategy is proposed and the tools from the non-smooth analysis theory are adapted to analyze the stability. Moreover, under the developed protocol, consensus can be realized after a finite transient time while avoiding the continuous information transmissions among agents. Finally, the effectiveness corroboration of the theoretical results are provided by the numerical simulation.