Dynamic Event-triggered Mechanism Research Articles

Secure Consensus of Multiagent Systems With DoS Attacks via Fully Distributed Dynamic Event-Triggered Control

This article investigates the secure consensus problem of general linear multiagent systems with denial-of-service (DoS) attacks. Owning to the existence of DoS attacks, it is challenging to investigate the event-triggered control of multiagent systems in a fully distributed manner. This article presents a novel dynamic event-triggered mechanism to alleviate the limited communication resources. Moreover, the designed mechanism is fully distributed and scalable owing to the introduction of some adaptive coupling weights. Since the DoS attacks have been considered in the event-triggered rule design, a novel adaptive parameter with an additional exponential term is adopted to deal with DoS attacks. The Lyapunov design also introduces such a term for the subsequent stability analysis. Sufficient conditions guaranteeing the asymptotic consensus of the studied system are developed in light of the controller’s parameters, duration, and frequency of the DoS attacks. Strict proof is provided to demonstrate that a secure consensus can be reached effectively under the proposed control mechanism. Furthermore, it is shown that the Zeno behavior can be excluded from the designed triggering mechanism. Finally, simulations on a multiagent system consisting of interconnected unmanned intelligent vehicles are conducted to verify the results.

Dynamic event-triggered adaptive NN consensus control for nonlinear multiagent systems with unknown measurement sensitivity

In this paper, the event-triggered adaptive neural network (NN) asymptotic consensus control problem is studied for nonlinear multi-agent systems (MASs) with unknown measurement sensitivity. A new distributed filter is designed to estimate the leader and solve the nondifferential problem of virtual controllers caused by the noncontinuous consensus error. The unknown nonlinear dynamics and measurement sensitivity are handled by using the NN approximators and adaptive estimation method, respectively. To avoid unnecessary data transmissions, a dynamic event-triggered mechanism (DETM) composed of the measurement and control channels is designed. Then based on backstepping technique, an asymptotic consensus controller is obtained. It is proved that the closed-loop signals are all bounded, and the consensus error asymptotically converges to the origin. Finally, to show the effectiveness of the developed control method, we apply the developed control method to multiple unmanned surface vehicles (USVs).

Robust tracking control for uncertain Euler–Lagrange systems via dynamic event‐triggered and self‐triggered ADP

AbstractThis article investigates the robust tracking control problem for a class of Euler–Lagrange systems in presence of parameter uncertainties and external disturbances. Through system transformation and theoretical analysis, an adaptive dynamic programming (ADP) algorithm with two adaptive neural networks (NNs) and a suitable triggering mechanism is proposed to attain the robust stability of the closed‐loop system. A single critic NN is leveraged to implement the approximate optimal controller design. Particularly, an NN‐based feedforward compensation is developed to cope with the uncertainties with unknown bounds. Two different triggering mechanisms are respectively constructed to reduce the budget of sampling, communication and computation, namely the dynamic event‐triggering mechanism (DETM) and the self‐triggering mechanism (STM). The DETM is utilized to decide the update of remote controller and critic NN weight, which can yield a larger inter‐event interval than the static event‐triggering mechanism. Also, the Zeno‐free behavior is guaranteed. Moreover, it is a novel attempt to introduce the STM into ADP design, which relaxes the demand of dedicated hardware online monitoring the event‐triggering condition. Then it is demonstrated that all signals in the closed‐loop system are uniformly ultimately bounded (UUB) via Lyapunov‐based stability analysis. Finally, a simulation example of 2‐link robotic system is implemented to verify the feasibility and effectiveness of the proposed algorithm.

Event-Triggered Underactuated Control for Networked Coupled PDE-ODE Systems With Singular Perturbations

An improved fuzzy event-triggered underactuated control strategy for networked coupled partial differential equation-ordinary differential equation (PDE-ODE) systems subject to singular perturbations is established. First, the networked coupled PDE-ODE systems are combined into an integrated system by representing the ODE and PDE states as a new state variable. Subsequently, a singular perturbed matrix is introduced to describe the multiple time-scale phenomenon of the system. In addition, an improved fuzzy controller is proposed to ensure the stability of the closed-loop coupled PDE-ODE systems based on boundary measurements. The novelties of the designed control strategy pertain to the following aspects: 1) The dynamic event-triggered mechanism is optimized; 2) an underactuated controller is proposed; and 3) the controller is constructed in a unified form. Finally, a hypersonic rocket vehicle's simulation is performed to demonstrate the method's effectiveness.

Stochastic Synchronization of Semi-Markovian Switching Cyber-Physical Impulsive Complex Networks via Dynamic Event-Triggered SMC

In this paper, a novel dynamic event-triggered sliding mode control (SMC) scheme is developed to investigate the stochastic synchronization of semi-Markovian switching cyber-physical complex network (SSCCN) with impulsive effects. First of all, the mode-dependent average dwell time (MDADT) and the transition probability (TP) are introduced to express the semi-Markovian switching signal, which makes the proposed model more applicable than other systems where only the average dwell time (ADT) switching is provided. Moreover, to prevent system uncertainty and unnecessary data transmission, a new dynamic event-triggered mechanism is incorporated into the design of SMC. In most of the existing event-triggered SMC strategies, the continuity of sliding mode surfaces for SSCCN is lost due to intermittent impulsive effects and stochastic switching in the system. Considering this problem, a piecewise mode-independent integral sliding function is put forward that takes into account the dynamic properties of the impulses through the proposed dynamic event-triggered mechanism. It can not only obtain the continuous trajectories of the impulsive networked system, but also significantly reduce the number of event triggers. Some rigorous analytical techniques have been developed to obtain the sufficient conditions required to ensure both the mean square synchronization (MSS) and almost sure synchronization (ASS) of SSCCN. Finally, some numerical examples are presented to demonstrate the effectiveness of the theoretical analysis.

Security Fuzzy Control of Nonlinear Semi-Markov Switching Systems With Event-Based Mechanism and Hybrid Cyber-Attacks

This article is concerned with the security <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{H}_{\infty}$</tex-math> </inline-formula> fuzzy control problem for Takagi–Sugeno (T–S) fuzzy semi-Markov switching systems (SMSSs) with event-based strategy and hybrid cyber-attacks. To efficiently use network resources and avoid unnecessary signal transmission, a new mode-dependent dynamic event-triggered mechanism (ETM), whose threshold parameter changes with varying states and modes is developed for each subsystem of fuzzy SMSSs. A more practical network environment subject to deception and denial-of-service (DoS) attacks is considered, and two Bernoulli distributed variables are adopted to characterize the randomly occurring hybrid attacks in a unified framework. By the mode-dependent Lyapunov function, sufficient conditions are attained to assure that the closed-loop system is stochastically stable with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{H}_{\infty}$</tex-math> </inline-formula> attenuation performance. Finally, the validity and superiority of the proposed theoretical approach is demonstrated via its application to the Duffing–Van der Pols oscillator.

Global Output-Feedback Stabilization for Uncertain Feedforward Nonlinear Systems via Dynamic Event-Triggered Control

In this brief, the global output-feedback stabilization is addressed for a class of uncertain feedforward nonlinear systems. By integrating a dynamic event-triggered mechanism, a novel observer-based control scheme is established, where a time-varying gain is introduced to cope with large uncertainties and sampling errors in the system. Under this control scheme, the global convergence is ensured for the resulting closed-loop system states. Different from the related results, the system states are intermittently monitored by imposing suspension time after each sampling, so that the inter-event intervals have a uniform positive lower bound, and the Zeno behavior is automatically ruled out. Additionally, an internal dynamic variable is incorporated into the triggering mechanism to further extend the inter-event intervals. Finally, the obtained results are extended to a class of feedforward nonlinear systems with unknown time-varying growth rates. A simulation example is given by applying the proposed scheme to a nonlinear liquid level control (LLC) resonant circuit system.

Dynamic event-triggered fault detection for rotary steerable systems with unknown time-varying noise covariances

This paper is concerned with the fault detection problem for the rotary steerable drilling tool system under unknown vibrations and limited computational resources. Firstly, the drilling tool system can be modeled by a nonlinear stochastic system with unknown time-varying noise covariances. Then, the dynamic event-triggered mechanism is introduced to save computational resources, and the caused transmission error is completely decoupled by nonuniform sampling. Subsequently, a novel unscented Kalman filter is proposed by combining the expectation maximization method to estimate states when noise covariances are unknown. A residual and an evaluation function are constructed to detect faults. Finally, a numerical simulation and an experiment on a drilling tool prototype validate the superior performance of the proposed fault detection scheme, which has lower missed alarm rates and consumes less time than existing methods.

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.

Dynamic event‐triggered control for delayed switched neural networks: A merging signal scheme

AbstractThis paper investigates the asynchronous control of delayed switched neural networks via a dynamic event‐triggering mechanism (DETM) and a merging signal scheme. Firstly, an improved DETM is proposed through adding an exponential decaying term into the triggering condition, which is proved to have a larger lower bound by comparison with the static event‐triggering mechanism (SETM) and the existing DETM. Next, a merging signal is constructed by introducing a time‐varying delay to combine the system switching signal with the controller switching signal, which is convenient to deal with the synchronous and asynchronous switching in a unified framework. Then, the closed‐loop system which integrates the proposed DETM with the merging signal is formulated. Moreover, by constructing multiple time‐dependent Lyapunov functionals, sufficient conditions which ensure the asymptotical stability of the resulting closed‐loop system are derived, and a design algorithm for the feedback controller is designed consequently. Finally, the validity and superiority of the proposed results are demonstrated by numerical examples.

Security-Based Control for Networked Interval Type-2 Fuzzy Systems With Multiple Cyber-Attacks: An Improved Dynamic Event-Triggered Scheme

This paper addresses the problem of dynamic event-triggered (DET) control for networked interval type-2 (IT2) fuzzy systems subject to multiple cyber-attacks, which contain deception attacks and aperiodic denial-of-service attacks simultaneously. Firstly, a multiple cyber-attack model is established for the IT2 fuzzy systems with multiple cyber-attacks and external disturbances. Secondly, an improved DET mechanism (DETM) is proposed to reduce the communication burden. Contrasting with existing works, by introducing two adjustable parameters into the novel DETM, the presented DETM has more flexibility in adjusting the data packet transmissions to conserve more limited network resources. Meanwhile, the Zeno behavior is probably excluded under the proposed DETM while preserving the system performance. Thirdly, imperfectly matched membership functions (MFs) are considered between fuzzy controller and IT2 fuzzy model, and the global boundary information of MFs and slack matrices are introduced to relax stability conditions. Besides, by constructing a proper Lyapunov-Krasovskii functional, sufficient conditions are obtained to ensure the exponentially mean-square stable of the IT2 fuzzy systems with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results.

Adaptive Terminal Sliding Mode Speed Regulation for PMSM Under Neural-Network-Based Disturbance Estimation: A Dynamic-Event-Triggered Approach

The speed regulation control issue of the networked permanent magnet synchronous motor system is investigated in this paper by utilizing a nonsingular terminal sliding mode control scheme. In order to remove the demand of the prior knowledge for possible lumped disturbance and parameter uncertainties in the permanent magnet synchronous motor system, an adaptive neural network is introduced into the proposed terminal sliding mode control scheme. Moreover, in order to ease the communication overheads of the networked system, a new dynamic event-triggered mechanism with considering the neural network estimation error is employed to schedule the signal transmission between the speed sensor and the remote sliding mode controller. The Zeno phenomena for the developed dynamic event-triggered mechanism is excluded via explicit analysis. It is further shown that by choosing suitable sliding mode parameters, the proposed control strategy can guarantee the convergence of the sliding variable into a practical sliding region as well as the ultimate boundedness of the speed regulation error. Finally, the feasibility and applicability of the proposed speed regulation strategy are demonstrated by simulation results and a real experiment.

Dynamic Event-Triggered H ∞ Filtering for NCSs Under Multiple Cyber-Attacks

This article considers the dynamic event-triggered <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{H}_{\infty}$</tex-math> </inline-formula> filtering problem for networked control systems (NCSs) under multiple cyber-attacks. By taking into account both denial-of-service (DoS) and deception attacks (DAs), a novel dynamic event-triggering mechanism (DETM) and the corresponding event-triggered filter are presented. The proposed DETM further reduces data transmissions and also guarantees the exclusion of Zeno behavior. By resorting to a piecewise Lyapunov functional (PLF), sufficient conditions are derived to ensure that the resulting filtering error system is globally stochastically exponentially stable with the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{H}_{\infty}$</tex-math> </inline-formula> performance in the presence of both DoS and DAs. A simulation example of a tunnel diode circuit system is displayed to illustrate the validity of the proposed event-triggered filter under multiple cyber-attacks.

Distributed Fault Detection and Dynamic Event-Triggered Consensus for Heterogeneous Multiagent Systems Under Deception Attacks

This paper focuses on the problem of distributed fault detection and leader-following output consensus for heterogeneous multiagent systems subject to deception attacks. During the information exchange and dissemination, a malicious attacker can make full use of specialized computer technology and launch stochastic deception attacks against some vulnerable agents over the network. The attack signals in actual operation tend to be energy-constrained, and Bernoulli distribution can be used to describe the random features. Taking the attack information into account, the distributed fault detection observer and the dynamic consensus compensator are designed in two separate steps. In order to reduce unnecessary information transmission, a dynamic event-triggered mechanism with output-dependent threshold is introduced to the adjustment of consensus protocol. According to Lyapunov stability theory and linear matrix inequality (LMI) techniques, sufficient conditions are derived for developing the model gains of the observer and the compensator. Finally, a simulation example of RLC circuit systems is provided to illustrate the effectiveness of the obtained theoretical results.

A Decentralized Learning Control Scheme for Constrained Nonlinear Interconnected Systems Based on Dynamic Event-Triggered Mechanism

This article presents a decentralized learning control method for a class of partially unknown nonlinear systems with asymmetric control input constraints and mismatched interconnections via a novel dynamic event-triggering condition. By employing an integral reinforcement learning strategy, the system drift dynamics can be avoided in the learning process. Meanwhile, a critic neural network is designed to obtain the approximated value function and tuned by using the gradient descent approach. Furthermore, a novel dynamic event-triggering condition is designed to determine the occurrence of an event by introducing a dynamic variable. By using the Lyapunov theory, all signals in the closed-loop system are proved to be uniformly ultimately bounded. Finally, we present a nonlinear interconnected system and an interconnected power system to verify the effectiveness of the proposed method.

Distributed Dynamic Event-Triggered Secon- dary Control for Islanded Microgrids With Disturbances and Communication De- lays: A Hybrid Systems Approach

This paper investigates the secondary control problem of islanded microgrid (MG) under hybrid systems framework. Owing to network-induced imperfections caused by communication and limited communication resources, we consider the event-triggered secondary control problem under time-varying delays. A hybrid dynamic event-triggering mechanism (DETM) is proposed to reduce the usage of communication resources, the event triggering interval is enforced to be lower bounded by strictly positive value. A hybrid closed-loop model is constructed, that incorporates the communication delays and event-triggering mechanism (ETM), and it facilitates stability and performance analysis. Lyapunov-based stability conditions are proposed, while the maximum allowable delay can be determined. Moreover, the proposed hybrid DETM ensures that the minimum event-triggering interval (METI) can be designable and pre-specified, even in the presence of disturbances, which is important for control implementation. Finally, the effectiveness of the proposed control strategy is illustrated by simulation examples.

Cooperative Fault-Tolerant Output Regulation of Linear Heterogeneous Multiagent Systems via an Adaptive Dynamic Event-Triggered Mechanism.

This article considers the problem of cooperative fault-tolerant output regulation of linear heterogeneous multiagent systems with actuator faults where the exosystem matrix is known by part of the followers. An adaptive dynamic event-triggered scheme is proposed to avoid continuous communication between followers, removing the assumption that global information should be known for controller design. Different from the existing open-loop estimation method for obtaining intermittent communication, the approach proposed in this article does not require that the system matrices of all agents be the same and known a prior. Compared with the existing static or periodic event-triggered mechanism (ETM), by introducing dynamic variables, a more general form than an exponential function, the proposed adaptive dynamic event-triggered condition provides the potential to save energy and obtain better performance. It is demonstrated that the suggested event-triggered control (ETC) method performs cooperative fault-tolerant output regulation for all followers in a completely distributed way with intermittent communication while excluding Zeno behavior. Finally, a simulation example is carried out to illustrate the efficacy of the suggested strategy.

Dynamic event-triggered sliding mode control for the uncertain discrete-time system using the reaching law

Based on the reaching law, this paper investigates the issue of dynamic event-triggered sliding mode control for uncertain discrete-time systems with disturbances. A dynamic event-triggered mechanism is proposed to enhance the data utilization rate, and an observer is introduced accordingly. An observer-based linear sliding surface is then designed. Furthermore, a sliding mode controller based on a chattering-free reaching law is designed to ensure the reachability of the sliding region. The stability of the closed-loop system, including quasi-sliding mode and error dynamics, is analyzed. Finally, two illustrative examples are presented to compare and validate this method.

Finite time event-triggered consensus of variable-order fractional multi-agent systems

This paper focuses on the finite time consensus issue for variable-order fractional multi-agent systems (FMASs), where each agent is characterized by the piecewise-smooth systems. Firstly, the new variable-order fractional difference inequality and finite time stability theorem are developed, which greatly extend some existing results. Secondly, a distributed control protocol is presented, where a new triggering function and an internal dynamic variable are constructed for designing the dynamic event-triggered mechanism (DETM) to enlarge average event execution times and reduce the consumption of system resources. Thirdly, based on the developed variable-order fractional inequalities and finite time stability theorem, the considered systems achieve consensus within a finite time. Furthermore, it is proved that the Zeno phenomenon do not occur. Finally, the circuit realization approach for the designed control protocol is proposed and simulation results are provided to verify the correctness of theoretical analysis.

Event-triggered adaptive neural networks tracking control for incommensurate fractional-order nonlinear systems with external disturbance

The event-triggered adaptive neural networks (NNs) tracking control issue is considered in this paper for a type of incommensurate fractional-order systems (IFOSs) with disturbance. Unlike the existing works for IFOSs, the hypothesis of disturbance-like function and the frequency distributed model are avoided in this study by utilizing the continuity of fractional-order derivative (FOD). Then, based on the radial basis function (RBF) NNs and backstepping method, the adaptive control scheme is proposed to ensure that the reference signal can be tracked by the system output, where the derivative order of adaptive laws does not depend on the one of IFOS. Additionally, to further reduce the burden of communication network, an exponentially convergent term is introduced into traditional dynamic event-triggered mechanism (ETM) and the Zeno behavior is avoided. Finally, two illustrative examples are exhibited to verify the performance of designed control scheme.