Dynamic Event-triggered Mechanism Research Articles

Observer-based asynchronous event-triggered control for interval type-2 fuzzy systems with cyber-attacks

This study investigates the observer-based asynchronous dynamic event-triggered control problem for networked interval type-2 fuzzy systems (IT-2 FSs) suffering from hybrid cyber-attacks, whereby the deception attacks (DAs) and the non-periodic denial-of-service (DoS) attacks are simultaneously considered. Contrasting with existing works, a new resilient dynamic event-triggering mechanism (DETM) is employed in the design process of the controller in the event of hybrid cyber-attacks. It is concluded that the resilient condition of DETM is adaptively varied based on current sampling, latest available packets, and a discrete dynamic function. Using a piecewise Lyapunov functional (PLF), new stochastically exponential stability conditions are developed to ascertain the link among asynchronous DETM, DAs, non-periodic DoS attacks and mismatched membership functions (MMFs). These results can further reduce the data transmissions and guarantee the exclusion of the Zeno behavior. The effectiveness of the concerned system under hybrid cyber-attacks is ultimately verified by a numerical simulation.

Dynamic event-triggered resilient state estimation for time-varying complex networks with Markovian switching topologies

This paper addresses a resilient state estimation problem for an array of nonlinear complex networks with switching topologies under the dynamic event-triggered mechanism (ETM). To reduce the unnecessary data delivery, the dynamic ETM is introduced to schedule the data delivery from sensors to estimators. The model of the switched complex networks is established by adopting a Markov chain which is better to reflect the characteristics of practical complex networks. A set of novel estimators is obtained by using the properties of Kronecker product combining with the Lyapunov–Krasovskii method, and some easy-to-check conditions are derived such that the dynamics of state estimation error satisfies the prescribed H∞ performance index. In addition, the parameters of the designed resilient state estimators can be acquired by solving a series of convex optimization problems. In the end, a simulation example is given to demonstrate the validity of the proposed theoretical results in this paper.

Distributed bipartite consensus for multi-agent systems with dynamic event-triggered mechanism

This paper address the distributed bipartite consensus problem of multi-agent systems (MASs) under undirected and directed topologies with dynamic event-triggered (DET) mechanism. The relationship among agents not only collaborative interaction but also competitive interaction are taken into account. A novel DET control protocol is raised with internal dynamic variables to guarantee that each agent can reach the bipartite consensus. Compared with the existing static triggering laws, the introduced DET strategy can significantly enlarge the interval time between two triggering instants. In addition, continuous information transmission in either controller updating or between agent and its neighbors is not demanded, which implies that the communication frequency can be extremely decreased. It is also proven that Zeno behavior does not occur. Finally, two numerical examples verify the validity of the presented theoretical results.

Co-design of output-based security control and dynamic event-triggered mechanism for NCSs under hybrid cyber attacks

This paper investigates output-based dynamic event-triggered control for networked control systems (NCSs), in which hybrid cyber attacks randomly occur in communication network. First, a gain adjustable dynamic output feedback (DOF) controller is designed for NCSs and relaxes state-available constraint in presence of three types of attacks, including stochastic deception attacks, replay attacks and aperiodic denial-of-service (DoS) attacks. Second, a output-based dynamic event-triggered mechanism (DETM) is designed to optimize limited network resources under the cyber attacks. Third, a new switched system is established to describe the effect of hybrid cyber attacks, the DOF controller and the DETM simultaneously. Then, criteria for guaranteeing asymptotically stability of the switched system are obtained. Furthermore, the co-design method of DETM and DOF controller is provided to maintain the NCSs stability. Finally, an example is presented to show the effectiveness of the proposed methods in this paper.

A distributed dynamic event-triggered mechanism to HMM-based observer design for [formula omitted] sliding mode control of Markov jump systems

This paper is devoted to investigating asynchronous state observer design for H∞ analysis of Markov jump systems with partial mode information through sliding mode control approach. In order to enhance the reliability and efficiency of communication network, a novel distributed dynamic event-triggered scheme is proposed. Firstly, due to partial information on the operation of system jumping modes, a continuous-time hidden Markov model (HMM) based asynchronous state observer relying on the triggered output measurement is designed, based on which an integral sliding surface function is proposed; Secondly, by proposing an asynchronous sliding mode control law, the finite-time reachability of estimated trajectories onto the predefined sliding surface is ensured; Thirdly, the stochastic stability with a prescribed H∞ disturbance attenuation level is analyzed for the considered closed-loop systems through linear matrix inequality; Finally, a numerical example is presented to verify the validity of the proposed control scheme.

Hybrid variables-dependent event-triggered model predictive control subject to polytopic uncertainties

This paper focuses on the model predictive control (MPC) issue where the measurable state is released under an event-triggered mechanism (ETM) to implement MPC over an infinite horizon. A new dynamic ETM (DETM) is devised to conserve network resources, which contains an additive internal dynamic variable (IDV), a multiplicative adaptively adjusting variable, a time-varying weighting matrix and several flexible scalars. The MPC problem is formulated as a ‘min–max’ optimisation problem (OP), where a hard constraint and robust positive invariant set on the predictive state/IDV are considered simultaneously. By resorting to a Lyapunov-like function that depends on the IDV, we put forward an auxiliary OP with matrix-inequality-based constraints. By the feasible solutions of such an auxiliary OP, the feedback gain matrix is designed which ensures the asymptotic stability of the closed-loop system. Two examples are presented to demonstrate the validity of the devised DETM and the DETM-based MPC algorithm. The study verifies that the devised DETM has advantages over an existing counterpart in conserving network resources while achieving the desired performance.

Dynamic Event-Triggered Impulsive Control for Stochastic Nonlinear Systems With Extension in Complex Networks

This study proposes a novel dynamic event-triggered impulsive control (ETIC) scheme to study the exponential stabilization of general stochastic nonlinear systems, where the impulsive sequence is determined by a dynamic event-triggered mechanism. The dynamic ETIC can effectively reduce controller updates and significantly save energy under the same decay rate compared to traditional static event-triggered impulsive generators. Additionally, there is a guaranteed positive minimum inter-event time for each sample path solution of systems. Furthermore, the proposed dynamic ETIC scheme is employed to stabilize stochastic complex networks based on the graph theory and the Lyapunov method. Finally, we provide two illustrative examples to verify the effectiveness and correctness of the proposed dynamic ETIC scheme.

Security Control for Multi-Time-Scale CPSs Under DoS Attacks: An Improved Dynamic Event-Triggered Mechanism

This article is concerned with the event-based security control problem for a class of multi-time-scale cyber physical systems (MTSCPSs) subject to DoS attacks. To tackle the difficulties caused by DoS attacks and the multi-time-scale feature (MTSF), a security control framework is developed to co-design the switched controller and event-triggered mechanism (ETM). An improved dynamic ETM is proposed, with which the closed-loop system can achieve a better control performance than traditional dynamic ETMs in the transient process. A novel <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -dependent Lyapunov-Krasovskii functional is also established, via which sufficient conditions are derived to ensure the <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 index of the closed-loop system and further cope with the ill-conditioned numerical issues generated by the MTSF. Finally, a simulation on a mini mining-tram drive control system is presented to demonstrate the correctness and merits of the proposed algorithm.

Event‐triggered state estimation for recurrent neural networks with unknown time‐varying delays

AbstractWe consider the problem of event‐triggered state estimation for recurrent neural networks subject to unknown time‐varying delays by proposing a robust dynamic event‐triggered state observer. A method based on a novel state observer and a dynamic event‐triggered mechanism (ETM) is proposed to provide robust state estimation of the delayed recurrent neural networks. The significance of the new dynamic ETM is that it helps to reduce unnecessary transmissions from the sensors to the observer. A sufficient condition for the existence of the dynamic event‐triggered state observer in terms of a convex optimization problem is proposed based on Lyapunov theory combined with free‐weighting matrix technique and some useful inequalities such as Wirtinger‐based integral inequality, Cauchy matrix inequality and reciprocally convex combination inequality. The effectiveness of the proposed estimation method is demonstrated by two numerical examples and simulation results. In contrast to the event‐triggered state estimation methods currently available in the literature, which require that the time delays are constant or unknown time‐varying but must be differentiable and event‐triggered conditions depend on continuous supervisions, the one in this article only requires the information of upper and lower bounds of the unknown time‐varying delays and the event‐triggered conditions depend on discrete supervisions, which provides more practicality and potential saving in network bandwidth.

Safety-critical dynamic event-triggered control of nonlinear systems

This paper is concerned with the problem of safety-critical dynamic event-triggered control (ETC) for nonlinear systems. A novel safety-critical dynamic ETC strategy is proposed to simultaneously guarantee event-triggered safety and stability based on the union of input-to-state safe barrier function (ISSf-BF) and input-to-state stable Lyapunov function (ISS-LF). Also, an appropriate dynamic event-triggered mechanism (DETM) is constructed, and Zeno phenomenon of ETC in the safety-critical control framework is definitely excluded based on the DETM constructed. Compared with the existing safety-critical control designed in the framework of continuous-time feedback control, the proposed strategy constructs safety-critical event-triggered controller and an DETM, which greatly alleviates the unnecessary waste of communication and computation resources. Finally, three examples are presented to demonstrate the effectiveness of the proposed design strategy.

Input-output finite-time control of Markov jump systems with round-robin protocol: An dynamic event-triggered approach

This article investigates the control problem of networked Markov jump systems (MJSs). First, to describe the asynchronization between the plant modes and the controller modes in MJSs, the hidden Markov model is introduced and the asynchronous control technique is developed. Next, the dynamic event-triggered mechanism (ETM) is utilized to decrease the frequency of data transmission. Moreover, the round-robin protocol (RRP) is introduced to reduce the amount of communicated data by allowing only one node to access the network. At last, the concept of input-output finite time stability (IO-FTS) is introduced and taken into consideration in the controller design. The highlight of this work is the introduction of both the dynamic ETM and the RRP to alleviate the communication load. Finally, a simulation example is proposed to illustrate the effectiveness of the theoretical results.

Event-triggered neural adaptive anti-disturbance control of nonlinear multi-agent systems with asymmetric constraints

The event-triggered adaptive control problem of stochastic nonlinear multi-agent systems subject to stochastic faults and asymmetric output constraints is investigated in this paper. Radial basis function neural networks (RBFNNs) are employed to adaptively approximate the unknown nonlinearities and changes in system dynamics model due to stochastic failures. By utilising a one-to-one nonlinear mapping, the asymmetric output constraints stochastic system is converted into a system without any constraints. Furthermore, to save the communication resources between controller and actuator, an improved dynamic event-triggered mechanism is developed, which contains threshold parameters and an exponential convergence term. Then, based on the stochastic Lyapunov function method, an event-triggered adaptive fault-tolerant controller is proposed for the considered systems. It is shown that the developed adaptive fault-tolerant controller can guarantee that all the signals remain semi-globally uniformly ultimately bounded while the output constraint is satisfied, even if the system is affected by stochastic failures. Eventually, the example results are provided to illustrate the effectiveness of the proposed control methodology.

Generalized proportional integral observer‐based event‐triggered control for frequency regulation in power systems with wind energy

AbstractThe article addresses a generalized proportional–integral observer (GPIO)‐based event‐triggered control (ETC) for load frequency problems in power systems with wind energy integration. The concept of static event‐triggered mechanism (ETM) with a fixed threshold parameter may be unreasonable in some engineering applications where the transmission rates are time varying as in the case with power systems. Therefore, in this work, a dynamic ETM is designed to dynamically adjust the threshold parameters over time to reflect the time‐varying transmission rates. The unmatched uncertainties are suppressed via high‐gain design while the external disturbance (wind speed) is estimated and attenuated by the GPIO‐based ETC. The proposed design ensures frequency and tie‐line power stabilization and saves the computational and communication resources more effectively than recently reported works in the field. The hybrid closed‐loop system's global bounded stability is theoretically proved and verified by simulation in three‐area interconnected power systems.

Dynamic event-triggered adaptive command filtered control for nonlinear multi-agent systems with input saturation and disturbances

This paper investigates the dynamic event-triggered adaptive command filtered control for the nonlinear high-order multi-agent systems with input saturation and disturbances. By designing a novel dynamic event-triggered adaptive command filtered control, computational burdens have been removed comprehensively. First, a dynamic event-triggered mechanism is designed, which can dynamically adjust the update frequency of controllers to reduce the computational burdens caused by the continuous updates of controllers. Moreover, the proposed approach can save communication resources and improve control performances simultaneously. Second, the command filtered control is studied to remove the computational burdens caused by the repeated differentiation of virtual control signals. Furthermore, input saturation and disturbances are handled concurrently. Finally, simulation results are given to validate the efficacy of the proposed approach.

Dynamic Event-Triggered Finite-Time H∞ Tracking Control of Switched LPV Aero-Engine Models

In this article, the transient <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> tracking performance, i.e., finite-time <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> tracking control, of switched linear parameter-varying (LPV) aero-engine models over a finite-time horizon is studied utilizing dynamic event-triggered method. For this purpose, a novel dynamic event-triggered mechanism (DETM) is constructed. It is shown that under the proposed method, transmission times of sampled information of the reference are determined by the designed DETM and transmission intervals can be adjusted with the variety of the tracking performance. The sampled information of the reference is updated when the event is triggered, and thus compared with traditional tracking methods, the transmitting cost can be reduced dramatically. An application of the control of aero-engines is demonstrated to show that the presented results are valid.

Dynamic Event-Triggered SMC of Multi-Agent Systems for Consensus Tracking

The dynamic event-triggered sliding mode control (SMC) method is used for the first time to address the consensus tracking problem of discrete-time multi-agent systems (MASs) in this brief. To avoid redundant data transmission, a dynamic event-triggered mechanism is introduced in the SMC. Considering the relationship between the leader and followers, a new sliding mode surface (SMS) related to the tracking error is designed. By designing a proper SMC law, sufficient conditions are obtained to ensure the accessibility of the specified SMS and consensus tracking. Finally, a group of comparative experiments are given to illustrate the validity of the proposed approach.

Periodic Event-Triggered Control for a Class of Nonminimum-Phase Nonlinear Systems Using Dynamic Triggering Mechanism

In this paper, the output feedback based periodic event-triggered control problem is considered for a class of nonminimum-phase nonlinear systems via dynamic event-triggering mechanism. When only the sampled-data output is known, a new periodic event-triggered control method is proposed via output feedback and the control input updates based on a discrete-time dynamic event-triggering condition. Despite the unstable zero dynamics, the proposed control method can asymptotically stabilize the hybrid control systems by closing the loop only when it is necessary. In contrast to the continuous-time static one, the proposed dynamic triggering condition has several advantages including the easier digital implementation and the larger average inter-event time interval. The delicate analysis gives the explicit expression of the maximum allowable sampling period, and the global asymptotic stability can be achieved for the hybrid control systems. Finally, the effectiveness of the proposed periodic event-triggered control method is verified by a numerical simulation.

A Secure Dynamic Event-Triggered Mechanism for Resilient Control of Multi-Agent Systems Under Sensor and Actuator Attacks

Information exchanges among interacting agents play a significant role in guaranteeing successful completion of the desired coordinated control tasks for a multi-agent system (MAS). Furthermore, these information exchanges are often performed over some open and resource-constrained communication networks, thereby making security and resource efficiency vitally important for various multi-agent coordinated control problems. This paper addresses a secure dynamic event-trigger-based resilient consensus control problem for an MAS in the presence of both sensor and actuator attacks. First, a distributed adaptive compensator is introduced for prediction of unavailable system states. Due to the existence of sensor and actuator attack signals, a secure dynamic event-triggered mechanism is then proposed, and a resilient control strategy is further devised for the paralyzed MAS. It is theoretically proved that the controlled MAS is asymptotically stable and asymptotic consensus is eventually achieved among the coordinated agents regardless of the attacks and constrained resources. Finally, three examples are provided to illustrate the effectiveness of the proposed strategy.

Robust cooperative output regulation of linear uncertain multi-agent systems by distributed event-triggered dynamic feedback control

In this paper, distributed state and output feedback control law based on the dynamic event-triggered mechanism are proposed to solve the robust cooperative output regulation problem for a class of general linear uncertain multi-agent systems (MASs) subject to external disturbances. The discrete-time control law proposed for each agent is equivalent to a discrete one and thus directly implementable in the digital platform. Our design can handle parametric uncertainties, reject external disturbances and track a dynamic leader while excluding the Zeno phenomenon by providing the existence of a lower bound for inter-event times of each agent, the efficiency of which is illustrated by a numerical example.

Learning‐based robust control methodologies under information constraints

Learning‐based robust control methodologies under information constraints