Dynamic Event-triggered Mechanism Research Articles

Non‐fragile control for dynamic event‐triggered networked systems with randomly occurring nonlinearities

This article focuses on the issue of non‐fragile control for a networked control systems (NCSs) with randomly occurring nonlinearities, where an advanced dynamic event‐triggered mechanism (DETM) is introduced. First, an improved DETM transmission strategy for NCSs is proposed. Based on the dynamic error of the system, the improved DETM can adaptively adjust the threshold to control the transmission of signals. The balance of the network bandwidth and control performance is excellently regulated by the adaptive threshold rather than a predetermined constant. Second, by taking the networked‐induced delay, DETM, randomly occurring nonlinearities and controller gain perturbation into consideration, a nonlinear system model is established. Next, sufficient stability conditions that can guarantee the mean‐square asymptotical stability are obtained based on the novel two‐side Lyapunov‐Krasovskii functional (LKF) and second‐order generalized free‐matrix‐based integral inequality (GFMBII), which contains more system information and can provide less conservative results. Finally, two numerical examples are presented to verify the advantages of the proposed method.

Dynamic event-triggered H∞ filtering for discrete-time singular networked control system subject to cyberattacks

This paper investigates the event-triggered filtering problem for the discrete-time singular networked control systems (DSNCS) with random cyberattacks. To more effectively utilize the limited network resource, a new dynamic event-triggered mechanism is proposed, which can effectively reduce network information transmission and save bandwidth on the premise of ensuring system performance. By considering the effect of the event-triggered mechanism and two types of cyberattacks, the filtering error system model has been constructed. Two independent random variables obeying the Bernoulli distribution are introduced to describe the two types of cyberattacks. Sufficient conditions that can guarantee the admissibility of the filtering error system have been developed with Lyapunov stability theory and LMIs techniques. Moreover, the co-design method is present in terms of LMIs to derive the parameters of dynamic event-triggered mechanism and the designed [Formula: see text] filter synchronously. Finally, an illustrative example is employed to verify the usefulness of the proposed method.

Resilient filter of nonlinear network systems with dynamic event-triggered mechanism and hybrid cyber attack

In this paper, the problem of H∞ resilient filter for nonlinear network systems with dynamic event-triggered mechanism and hybrid cyber attack is discussed. The Takagi-Sugeno (T-S) fuzzy technique is applied to deal with the nonlinearity of network systems. For the obtained T-S fuzzy model, the system measurement output is assumed to transfer to the filter by network channels. A novel dynamic event-triggered communication scheme is proposed to improve the utilization of network resources. In addition, Bernoulli binomial distribution are used to simultaneously describe the phenomenon of deception and DoS attack. Multi-channel network delay is solved by the method of combining delay division and segmented Lyapunov-Krasovskii functional. The co-design conditions of the H∞ resilient filter based on dynamic event-triggered are given by the form of linear matrix inequalities (LMIs), and ensures that the error filtering system is stochastically stable under the H∞ performance index. Finally, the effectiveness and superiority of the filter are verified by the joint simulation of Matlab and Carsim.

Fault Diagnosis for Networked Switched Systems: An Improved Dynamic Event-Based Scheme.

The issue of fault detection and isolation (FDI) under an event-triggered mechanism (ETM) is investigated for switched linear systems. An improved dynamic ETM (DETM), which includes some existing ETMs as special cases, is devised. Such a DETM contains two internal dynamic variables (IDVs), the mode information and seven adjustable parameters, and thus is flexible in adjusting the data packet transmissions to save network resources. The aim is to design a fault detection (FD) filter (FDF) and fault isolation filters (FIFs) such that the resultant filtering error systems are exponentially stable with prescribed exponential H∞ performance. A new Lyapunov function, which depends on the switching mode and two IDVs, is constructed. By utilizing the Lyapunov method and the average dwell time approach, sufficient conditions are derived to guarantee the existence of the desired FDF and FIFs, whose design methods are given accordingly. A numerical example is provided to demonstrate the effectiveness of the FDI method and the superiority of the devised DETM in reducing the waste of network resources while maintaining the FD filtering performance.

Cooperative Output Regulation Problem for Multiagent System Under Directed Topology Using Dynamic Triggering Strategy

This brief focuses on cooperative output regulation (COR) problem for linear multiagent systems (MASs) under the directed topology. The fully distributed event-triggered control protocol is designed to solve COR problem. In order to reduce the communication frequency, the dynamic event-triggered mechanism is proposed by introducing positive internal variable. One main advantage is that the method inherits the advantages of event-triggered control and adaptive control to deal with the COR problem, and does not depend on global information. At last, a numerical example is given in the supplementary material to verify the validity of the obtained results.

Dynamic Memory Event-Triggered Adaptive Control for a Class of Strict-Feedback Nonlinear Systems

This brief presents a dynamic memory event-triggered mechanism based adaptive control strategy for a class of strict-feedback nonlinear systems. Firstly, the dynamic memory event-triggered mechanism (DMETM) is established, rigorous proof demonstrates that the triggering intervals of the proposed DMETM are larger than that of the memoryless dynamic event-triggered mechanism. Furthermore, the adaptive control strategy is designed via the dynamic surface control, by which the “explosion of complexity” in the backstepping design process is avoided. Additionally, the proposed DMETM based adaptive dynamic surface controller can guarantee the closed loop system to be semi-globally uniformly ultimately bounded (SGUUB). Finally, the simulation results illustrate the validity of the proposed control strategy.

Codesign of Dynamic Event-Triggered Gain-Scheduling Control for a Class of Nonlinear Systems

This technical article investigates the problem of event-triggered gain-scheduling control of nonlinear systems. The considered class of nonlinear systems is such that an equivalent local polytopic model is obtained. By following the codesign approach, it is performed the simultaneous design of the dynamic event-triggering mechanism (ETM) and the gain-scheduled controller parameterized in terms of state-dependent scheduling functions. As the state information is only available to the controller at specific instants determined by the ETM, the scheduling functions of controller and plant polytopic model are asynchronous. To cope with this drawback, the trigger function of the dynamic ETM is appropriately defined to mitigate the influence of asynchronous scheduling functions in the Lyapunov stability-based analysis, allowing to derive a less conservative codesign condition. A convex optimization problem with linear matrix inequality constraints is proposed to perform the codesign and to enlarge the interevent times. Also, it is shown that there exists a lower bound for the interevent times, which prevents Zeno behavior. Numerical examples are provided to illustrate the advantages of the proposed dynamic event-triggered control codesign approach over emulation-based approach and its static counterpart.

Adaptive dynamic event-triggered deployment control for space triangle tethered formation system with external disturbance

Space tethered system has been widely investigated because of its extensive applications in space observation, debris removal, and space solar power station, etc. Yet, due to the system coupling nonlinearities, unknown disturbances, and on-board limited communication constraints, the deployment control of the spacecraft system is still challenging. In this paper, an adaptive integral sliding mode controller is designed by using neural network estimator, barrier function and event-triggered mechanism, which ensures that the system deploys to the specified configuration in finite time. Giving that the lumped disturbances are bounded by an unknown boundary, the gain of the switching term is tuned by the barrier function such that the gain-overestimation problem can be avoided. Then, the dynamic event-triggered mechanism updates the control signal non-periodically between the controller and the actuator, thus communication resources can be saved. Moreover, the stability of the closed system with and without event-triggered mechanism is analyzed. Finally, simulation tests are carried out to exhibit the effectiveness of the proposed control scheme.

Consensus of linear multi-agent systems by distributed event-triggered strategy with designable minimum inter-event time

This paper investigates the consensus problem of multi-agent systems under the event-triggered control with designable minimum inter-event time, in which each agent has an identical linear dynamic model. The goal is to devise a novel control method which can not only reduce actuator consumption but also guarantee the state consensus of the controlled systems. Two event-triggered mechanisms are considered, namely, the static event-triggered mechanism and the dynamic event-triggered mechanism. To this end, a novel distributed static event-triggered control algorithm is presented at first. Then the distributed dynamic event-triggered control algorithm is developed. The major superiority of the presented distributed static and dynamic event-triggered control algorithms is that the controller of each agent is only triggered at its own event time, which effectively reduces the update frequency of the controller in practice. Further, the minimum inter-event time is adjustable by the parameter of the parametric Lyapunov equation, which makes it easier to find a trade-off between the inter-event times and the control performance of the controlled system. Subsequently, it is proved that the consensus of the multi-agent systems is reached asymptotically and non-occurrence of the Zeno phenomenon is proved. The superiority of the designed algorithms is testified by the simulation.

Event-triggered asynchronous synchronization control for switched generalized neural networks with time-varying delay

The present research is concerned with the ℓ2-ℓ∞ synchronization control for discrete-time switched generalized neural networks subject to time-varying delay. Distinct from the existing correlative results, a novel synchronization paradigm is established, in which the designed synchronization controller only contains the information of neuron states and switching signal at the certain triggering instants scheduled by the designed dynamic event-triggered mechanism. Also, an interesting asynchronous problem caused by the asynchronization of the switching and triggering actions is taken into consideration. For reducing the conservativeness of the conventional approaches, the time-dependent Lyapunov–Krasovskii functional for the resultant asynchronous situation is then constructed, and the correspondent sufficient conditions are formulated to ensure the exponential stability and weighted ℓ2-ℓ∞ performance of the concerned synchronization error systems. Finally, the applicability and superiority of the developed synchronization technique are substantiated with two simulation examples.

Dynamic Event-Triggered Control of Singularity-Perturbed Dynamic Networks and its Application

In this brief, the dynamic event-triggered control is investigated for a novel class of singularity-perturbed dynamic networks (SPDNs) with multi-time-scale. First, for a single agent, the two-time-scale characteristic described by a small singularity-perturbed parameter (SPP) is considered. Then, every agent is equipped with a personalized SPP <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon _{i}$ </tex-math></inline-formula> , which denotes the multi-time-scale characteristic of the SPDNs. Owing to the SPP <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon _{i}$ </tex-math></inline-formula> , the restriction in most the existing works that every agent must have the same SPP can be removed. Further, the networks with single-time-scale, two-time-scale, or multi-time-scale can all be modeled by the proposed SPDNs by selecting an appropriate value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon _{i}$ </tex-math></inline-formula> . A state feedback controller based only on the slow dynamics information is considered. Besides, a dynamic event-triggered mechanism (ETM), where the threshold parameters are adjusted as the slow state fluctuations, is introduced to reduce the communication frequency reasonably. By means of Lyapunov stability theorem and a decoupled method, some stability conditions that are independent of the scale of the SPDNs are obtained. Finally, the effectiveness and advantages of the proposed method over existing ones are demonstrated through an electronic circuit system.

Fully Distributed Event-Triggered Bipartite Consensus of Linear Multi-Agent Systems With Quantized Communication

This brief considers fully distributed event-triggered bipartite consensus for linear multi-agent systems (MASs) with quantized information in leader-following network. First, a control strategy integrated of logarithmic quantizer and dynamic event-triggered mechanism (DETM) is proposed. Then, depended on a connected structurally balanced signed graph, a novel fully distributed control law with dynamic coupling gains is well-developed and discussed, under which agents are not required to know a priori knowledge of any global information. Second, by utilizing Lyapunov stability theory, some criteria for bipartite consensus with relative quantized state measurements are derived. Furthermore, it is shown that the Zeno behavior can be eliminated effectively. Finally, numerical studies are given to illustrate the validity of the theoretical findings and the advantage of proposed control strategy.

Dynamic Event-Triggered Bipartite Consensus of Multiagent Systems With Estimator and Cooperative-Competitive Interactions

In this brief, the bipartite consensus problem of linear multi-agent systems with a dynamic event-triggered protocol is studied. A distributed controller with a cooperative-competitive mechanism and estimated states is first designed, and a dynamic event-triggered mechanism proposed in which the triggering threshold is dynamically updated by the designed auxiliary equation. Under this control strategy, the systems only need the states of the agent and neighboring agents at the triggering instants. At the same time, the estimator is considered to reduce the states deviation of multi-agent systems between adjacent triggering instants. Moreover, bipartite consensus can be achieved without Zeno behavior. Finally, the feasibility of the proposed method is illustrated in a unicycle model.

A resilient optimized dynamic event-triggered mechanism on networked control system with switching behavior under mixed attacks

This paper studies the stability problem and H∞ performance of networked control system (NCS) in the presence of mixed attacks by developing an improved event-triggered mechanism (ETM). Firstly, both aperiodic denial of service (DoS) attacks and random deception attacks are encountered for investigating system dynamic behavior. Then, a resilient optimized dynamic event-triggered mechanism (RODETM) is proposed for reducing the unnecessary costs of system operation and mitigating the impact caused by attacks. On this basis, the standard NCS is reformulated into a switched system under the mixed attacks. Further, using the piecewise Lyapunov-Krasovskii functional method, average dwell time scheme and the linear matrix inequality (LMI) method, some sufficient conditions with control design implementation are obtained, which can ensure the exponential stability with the expected prescribed H∞ performance index of the studied system. Finally, the effectiveness of the proposed approach is demonstrated by using a numerical simulation with comparative analysis.

Event-Triggered Attitude-Orbit Coupled Fault-Tolerant Control for Multi-Spacecraft Formation

In this paper, the attitude-orbit coupled control problem for multi-spacecraft formation with limited communication capability and actuator failure is investigated. For the purpose of solving this problem, an event-triggered attitude-orbit coupled fault-tolerant control strategy is proposed. First, an integrated nonlinear dynamic model including the coupling characteristics of the attitude and orbit is established based on the Kane equation. Second, the nonlinear dynamic model is linearized at the reference state to facilitate the controller design. Third, a dynamic event-triggered mechanism is designed and an event-triggered fault-tolerant control law is developed. The stability of closed-loop control systems can be ensured under the designed control law and a sufficient condition that Zeno’s behavior can be avoided is presented. Finally, simulation results are given to show the effectiveness of the proposed control method.

Event-Triggered Antidisturbance Control Design for Aeroengine Systems via Switched Models

In this paper, an event-triggered antidisturbance (ETAD) control scheme is presented for a category of aeroengine control systems (AECSs) involved in multiple disturbances. First, an AECS in this category is described by a switched model at a series of steady-state points. Then, a dynamic event-triggered mechanism is introduced by constructing the ET condition based on the control input directly, saving the signal transmission resource from the controller to the AECS. Next, a switching law with sampling is developed, economizing the signal transmission resource from the switching law to the AECS. Furthermore, based on the ET mechanism and switching law, an antidisturbance controller is designed to compensate for or suppress the influence of the multiple disturbances on the AECS. Also, under the ETAD control approach, relative theoretical conditions are established to save the signal transmission resource and to suppress or compensate multiple disturbances. Finally, using a hardware-in-loop platform with a switched aeroengine model inserted, a simulation is implemented to validate how the established ETAD control strategy is effectively applied to the AECS.

Set-membership filtering for two-dimensional systems with dynamic event-triggered mechanism

In this paper, the set-membership filtering problem is investigated for a class of two-dimensional (2-D) shift-varying systems described by the general Fornasini-Marchesini second model with a dynamic event-triggered mechanism. The sensors are communicated with the remote filter through a communication network of limited bandwidth. In order to improve the efficiency of utilizing the network resources, a dynamic event-triggered mechanism is exploited for the 2-D shift-varying system, and a set-membership filter is then designed for 2-D systems subject to unknown-but-bounded noises so that the actual system state is guaranteed to reside within an optimized ellipsoidal set. By means of the mathematical induction technique and the set theory, sufficient conditions are derived to ensure the existence of the desired set-membership filter. Furthermore, the filter gains are obtained by solving a set of optimization problems subject to ellipsoidal constraints. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed filter design method.

Zonotopic fault detection for discrete-time systems with limited communication capability and sensor nonlinearity

In this paper, the fault detection filter (FDF) design problem based on a dynamic event-triggered mechanism (DETM) is investigated for discrete-time systems with signal quantization and sensor nonlinearity. In order to conserve the limited network resources, a newly event-triggered mechanism with dynamic threshold is adopted to reduce the number of transmitted data through network more effectively. With the consideration of DETM, signal quantization and sensor nonlinearity, a fault detection filter is constructed to achieve the robustly asymptotic stability of established model with expected fault detection objective. In addition, by influence of DETM, external interference and quantization errors, a zonotopic residual evaluation mechanism is constructed to detect the occurring fault of plant. Finally, a practical example is provided to illustrate the effectiveness of proposed design approach.

Dynamic event-triggered state estimation for time-delayed spatial-temporal networks under encoding-decoding scheme

This paper is concerned with the dynamic event-triggered state estimation problem for a class of spatial-temporal networks (STNs) with time-varying delays under an encoding-decoding strategy. For the sake of reducing the unnecessary resources wastes, we establish a dynamic event-triggered mechanism to determine whether the current measurement output data is transmitted to the filter, where the threshold is dynamically adjusted according to a certain rule. In order to enhance the robustness of signal transmission, an encoding-decoding strategy is exploited in the process of the data transmission. To be specific, the original signals encoded as a bit string are transmitted through binary symmetric channels with certain crossover probabilities and then restored by a decoder at the receiver. By constructing Lyapunov-Krasovskii functional, we obtain a sufficient condition to ensure that the estimation error system is exponential mean square ultimately bounded. Subsequently, the desired state estimator is designed in terms of the solution to a certain matrix inequality. Finally, a numerical example is shown to demonstrate that the proposed state estimator is valid for time-delayed STNs.

Observer-based dynamic event-triggered control for nonstrict-feedback stochastic nonlinear multiagent systems

In this paper, the consensus tracking control problem is investigated for stochastic nonlinear multiagent systems with nonstrict-feedback structure and unmeasurable states. Firstly, by proposing an event-triggered estimator, all followers not only can estimate the signal of leader, but also can avoid the continuous communication between agents. Then, an observer is designed to estimate the unmeasurable states. Based on backstepping and variable separation approach, an adaptive neural control strategy is proposed to deal with nonstrict-feedback nonlinearities. Furthermore, a modified dynamic event-triggered mechanism is developed to reduce the number of controller executions. Based on barrier Lyapunov function, an adaptive neural compensation control scheme is designed to tackle the input saturation and the state constraints of multiagent systems. Finally, it is confirmed that the proposed event-triggered adaptive controller can guarantee the convergence of consensus tracking errors and the semiglobal boundedness of all signals in the closed-loop system.