Event-triggered Parameters Research Articles

Dynamic event-triggered adaptive security sliding mode control for singular systems with unknown deception attacks

This paper studies the problem of dynamic event-triggered adaptive security sliding mode control (SMC) for singular systems with deception attacks. First, due to limited network resources, a dynamic event-triggered scheme (DETS) is adopted to reduce signal transmission. Second, the deception attacks which make the system unstable are modeled as a nonlinear function. Third, some sufficient conditions are given to assure that the overall system is admissible with [Formula: see text] performance and a method is proposed to design the controller gain and the event-triggered parameter. Fourth, a novel adaptive SMC law is provided to ensure the reaching condition of the sliding surface. Finally, a practical example is employed to show the validity of the designed method.

Event-Triggered Distributed Hypothesis Testing for Multiagent Networks Based on Observations Cumulation.

This article is concerned with the distributed hypothesis testing problem for multiagent networks, where a group of agents aim to learn an optimal hypothesis set via informative observations and event-triggered communication. Within this framework, a new event-triggered distributed hypothesis testing algorithm based on cumulation of historical observations is proposed. Theoretically, it is proven that due to the introduction of cumulation of historical observations, the proposed algorithm can always ensure the convergence whatever the event-triggered parameters are selected. This convergence result is different from that of the existing algorithm without involving historical observations, where the event-triggered parameters should satisfy a specific design condition to ensure the convergence of the algorithm. In addition, an explicit description of the convergence rate of the proposed algorithm is provided. Finally, the effectiveness of the algorithm is demonstrated through simulation examples.

Event-triggered nonlinear state estimation with quantized innovations

This paper proposes an event-triggered (ET) estimator with quantization mechanism to relieve the bandwidth and energy limitations of wireless sensors, where the ET strategy reduces the overall communication rate of the system, and the quantization mechanism mitigates the instantaneous bit rate constraint. Then, Gaussian approximation is applied to derive the analytical form of the minimum mean squared error (MMSE) estimator under the event-triggered strategy and quantization mechanism. Furthermore, the relationship between the event-triggered parameter and the communication rate is explicitly established. Finally, theoretical results are validated through some simulations on a target tracking system.

Improved event-based fault detection filter for networked fuzzy systems under DoS attacks

This paper investigates an improved event-based fault detection method for networked fuzzy systems under denial-of-service (DoS) attacks. In order to solve the bandwidth occupation problem of communication network, a resilient event-triggered transmission strategy is developed. Additionally, a fault detection filter is designed to estimate the time of fault occurrence by using the residual signal. Under this framework, a novel Lyapunov functional related to attack parameters is established to analyze the exponential convergence of the error signals, and the filter gains and event-triggered parameters are obtained by solving linear matrix inequalities. The designed functional reduces the conservatism of the stability criteria significantly in contrast with the previous discontinuous Lyapunov functionals. Finally, a simulation example is provided to verify the effectiveness of the proposed method.

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.

Fuzzy PD-sliding mode control design for networked system with time delays

This research specifically addresses the problem of sliding mode control (SMC) in a particular group of T–S fuzzy systems that experience output disturbances and time delays using a networked control system. First, a model for a proportional–derivative sliding mode observer (SMO) is established, subsequently followed by the design of a controller based on SMO to maintain closed-loop system stability. The authors establish a novel mechanism to optimize the bandwidth utilization of the communication network by introducing a newly adjusted event-triggering parameter. After that, addressed a linear matrix inequality (LMI) problem to determine the controller gain and observer coefficients. This was done to guarantee the asymptotic stability of the closed-loop plant. Furthermore, the authors were able to directly identify the disturbances for these plants using the proposed descriptor SMO. Moreover, a parameter-based novel event-triggered scheme, along with a new resultant closed-loop system, will be employed to modify trigger frequency parameters within a unified framework. The controller gains will be determined by solving a linear matrix inequality, subject to certain conditions that ensure sufficiency. These conditions will be deduced to ensure asymptotic stability. In the final section, the authors presented examples from the Wind Energy System (WES) that illustrate the feasibility and effectiveness of our proposed methodology.

Dynamic Event-Triggered Sensor Fault Interval Estimation and Accommodation for Aeroengine

This paper concerns with the dynamic event-triggered fault interval estimation and accommodation for aeroengine sensors. Firstly, a dynamic event-triggered based robust augmented state observer is designed to reconstruct sensor fault for an aeroengine subject to external disturbance and measurement noise. Next, the event-triggered parameters and fault-tolerant controller (FTC) are co-designed based on the obtained observer gains to save communication resources. Moreover, the interval estimation of sensor fault is achieved via reachability analysis. Eventually, the designed scheme is tested with aeroengine Hardware-in-the-loop (HIL) experiment, which illustrates its potential in aeronautical engineering.

Resilient event-triggering adaptive neural network control for networked systems under mixed cyber attacks

This paper addresses the resilient event-triggering adaptive neural network (NN) control problem for networked control systems under mixed cyber attacks. Compared with the conventional event-triggered mechanism (ETM) with constant threshold, a novel resilient ETM is designed to withstand the affect of denial-of-service attacks and conserve communication resources. Different from the energy-bounded deception attacks, an unknown state-dependent nonlinear attack signal is considered in this work. To identify the deception attack, the NN technique is utilized to approximate the unknown attack signal. Subsequently, an adaptive controller is established to compensate for the malicious affects of deception attacks on the system. Furthermore, sufficient conditions for the boundedness of the system are derived via applying the Lyapunov functional, and a co-design strategy for control gain and event-triggering parameter is provided. Finally, the feasibility of the proposed approach is validated through a robot manipulator system.

Hybrid event-triggered control for networked switched Takagi–Sugeno fuzzy systems with aperiodic DoS attacks

This article investigates the event-triggered control problem for networked switched Takagi–Sugeno fuzzy systems (NSTSFSs) with denial of service (DoS) attacks. First, an attack-instant-constrained hybrid event-triggered mechanism (ETM) is proposed, which uses the acknowledgment character (ACK) detection scheme. It can describe the triggering schemes under different attack intervals and modify the triggering frequency based on the performance of the system. Second, a new segmented Lyapunov function is designed that takes into account the asynchronous behavior of system and controller modes, as well as DoS frequency and duration constraints. Then, sufficient conditions are provided to ensure the exponential stability of the system and have an H∞ performance. Furthermore, a collaborative design scheme is proposed to obtain controller gains, the switching law, and event-triggered parameters. Finally, the accuracy and effectiveness of this method are verified through two simulation examples.

Refined Dynamic Event-Triggering Cluster Consensus of Multiagent Systems With Fixed/Switching Topology.

This article is concerned with cluster consensus control of multiagent systems (MASs) with the fixed/switching topology under a dynamic event-trigger (DET) mechanism. A refined sampled-data-based DET scheme is proposed by introducing two dynamically adjusting threshold parameters to distinguish the different transmission requirements for neighboring agents intra and outer cluster. Faced with the difficulties of acquiring full state information among spatially distributed agents, output feedback is employed to construct cooperative control protocols. Both fixed and switching topologies are considered to execute the designed DET-based cooperative cluster consensus control protocols. By constructing appropriate Lyapunov-Krasovskii functionals (LKFs), some sufficient criteria in terms of matrix inequalities for the cluster consensus of MASs are derived, which can ensure that the error system with the proposed DET-based control strategy is asymptotically stable. Facing the nonconvex issue induced by output feedback, a particle swarm optimization (PSO)-based control design algorithm is novelly developed to calculate the control gains and event-triggering parameters jointly based on the derived stability criteria. The elements of the matrix variables are valued stochastically in certain ranges and the fitness function is designed as the accumulation of the weighting value of each matrix inequality. Finally, an application of multiple satellites formation flying is applied to numerically illustrate the effectiveness of the cluster consensus control strategy with the designed DET mechanism.

Event-Triggered Reverse Attacks on Remote State Estimation

Security issues in cyber-physical systems have attracted increasing attention in recent years. In this paper, a security problem in a remote estimation application is considered, where an attacker tries to degrade estimation performance via malicious attacks. In our scenario, a smart sensor transmits its innovation to a remote estimator with a residue-based false data detector. Instead of assuming that the attacker launches a consecutive man-in-the-middle attack, we consider the case with intermittent attacks. Reverse attack is a simple attack strategy, which enables an attacker to change signs of the innovation sequences. Therefore, owing to the above reasons, an event-triggered reverse attack strategy is proposed to degrade system performance. First, the stealthiness of the event-triggered linear deception attack strategy is studied. Then, the evolution of the estimation error covariance is computed and the reverse attack is proven to be the optimal linear deception attack. We demonstrate that our event-triggered reverse attack is more destructive than a random reverse attack. Furthermore, a convex optimization problem is established to design event-triggered parameters. Comparisons of attack strategies are provided in a numerical example to validate the superiority of the reverse attack.

Event-triggered delayed impulsive control for functional differential systems on networks

This article investigates the stability of functional differential systems on networks adopting event-triggered multi-delayed impulsive control. We construct a new event-triggered mechanism (ETM) type using the Lyapunov function and the network topology. Combined with the ETM and multi-delayed impulsive control, in which the impulsive jumps are related to the current and past states, we propose a multi-delayed event-triggered impulsive control strategy. This controller will execute the control tasks only when the systems violate the preset ETM. In the view of the Razumikhin method and the graph theory, some criteria are given to avoiding Zeno behavior under this ETM and achieving exponential stability, which is related to the event-triggered parameters, network topology, and impulsive intensity. As an application of our theoretical results, a class of coupled oscillation systems is considered and numerical simulations are presented to verify the practicability and effectiveness.

Event-triggered hybrid impulsive control for synchronization of fractional-order multilayer signed networks under cyber attacks

In this paper, we consider the exponential bipartite synchronization (EBS) problem of fractional-order multilayer signed networks with time-varying delays (FO-MSNT) under random cyber attacks. In contrast to the existing literature, the proposed hybrid event-triggered controller combines the advantages of feedback controller and impulsive controller, and the event-triggered condition is constructed by applying the network topology and the Lyapunov function of the subsystem, rather than the state function of the subsystem. Based on the Lyapunov–Razumikhin method and the graph theory, some sufficient conditions for achieving EBS of FO-MSNT under cyber attacks which are related to the topology of networks, the event-triggered parameters, the order of fractional derivative and the signal sent by the enemy are obtained. Furthermore, fractional-order coupled Chua’s circuits model and fractional-order power systems built on MSNT are established and the EBS issues under cyber attacks are analyzed. Numerical examples and simulations are provided to show the validity of our theories.

Battery State of Charge Estimation with Event-Triggered Parameter Identification

Battery State of Charge Estimation with Event-Triggered Parameter Identification

Event-Triggered Learning-Based Fault Accommodation for a Class of Nonlinear Interconnected Systems.

In this article, a distributed learning-based fault accommodation scheme is proposed for a class of nonlinear interconnected systems under event-triggered communication of control and measurement signals. Process faults occurring in the local dynamics and/or propagated from interconnected neighboring subsystems are considered. An event-triggered nominal control law is used for each subsystem before detecting any fault occurrence in its dynamics. After fault detection, the corresponding event-triggered fault accommodation law is utilized to reconfigure the nominal control law with a neural-network-based adaptive learning scheme employed to estimate an ideal fault-tolerant control function online. Under the asynchronous controller reconfiguration mechanism for each subsystem, the closed-loop stability of the interconnected systems in different operating modes with the proposed event-triggered learning-based fault accommodation scheme is rigorously analyzed with the explicit stabilization condition and state upper bound derived in terms of event-triggering parameters, and the Zeno behavior is shown to be excluded. An interconnected inverted pendulum system is used to illustrate the proposed fault accommodation scheme.

Event-triggered output feedback control design for polynomial fuzzy systems

This paper presents a novel approach to event-triggered output feedback control of polynomial fuzzy systems that exhibit unmeasurable system states. To stabilize the system state, a fuzzy model-based event-triggered control scheme is proposed based on output measurement information. The transmission frequency is modulated using a periodic event-trigger protocol, which is scheduled by resorting to a set of historically released packets to ensure better dynamic performance. The event-triggering condition uses the current samples to determine the next trigger and also takes into account the triggering time-dependent gain parameter, thereby significantly reducing network burden. The proposed approach ensures the existence of both polynomial controller gain and event-triggered parameters by satisfying sufficient conditions based on the sum-of-squares approach and the polynomial fitting approximation algorithm. The addressed system’s stability conditions are solved using MATLAB SOSTOOLS. Three numerical examples, including an invented pendulum model, illustrate the superiority and applicability of the methodology. The main contributions of this work are the introduction of a triggering instant dependent periodic event-triggered output feedback control design, which reduces network traffic and enhances dynamic performance. The approach is validated through numerical examples, which demonstrate its superiority and applicability.

ET-PDA: An event-triggered parameter distributed accelerated algorithm for economic dispatch problems

In this paper, we consider a distributed economic dispatch problem (EDP) in smart grids, where each generator only communicates with its neighbors and minimizes its own cost in the presence of network-wide equality constraints and local capacity limits. Distributed algorithms to solve this problem have become an attractive focus of engineering research due to their multiple advantages. Many existing methods are time-triggered, whereas few works have been dedicated to solving the problem using an event-triggered approach. This problem gets more challenging when further accelerated convergence is desired. To solve such a problem, we carefully design an event-triggered parameter distributed accelerated algorithm, named as ET-PDA. On the one hand, the choice of different parameters in ET-PDA will lead to different momentum (Nesterov or heavy-ball) methods, which facilitates the accelerated convergence of the algorithm. On the other hand, the event-triggered mechanism in ET-PDA makes the time gap between two continuous interaction moments of each generator larger than the iteration interval, contributing to improved communication efficiency. In particular, ET-PDA achieves linear convergence when the local cost function of each generator is smooth and strongly convex, moreover, it precludes Zeno-like behavior. The effectiveness of ET-PDA is also verified through a series of simulation experiments.

Improved Event-Triggered Dynamic Output Feedback Control for Networked T-S Fuzzy Systems With Actuator Failure and Deception Attacks.

This article addresses the problem of event-triggered dynamic output feedback controller design for networked Takagi-Sugeno (T-S) fuzzy systems subject to actuator failure and deception attacks. In order to save network resources effectively, two event-triggered schemes (ETSs) are introduced to test whether the measurement output and control input are transmitted under network communication. While the ETS brings advantages, it also leads to a mismatch between the premise variables of the system and the controller. To solve this problem, an asynchronous premise reconstruct method is considered, which relaxes the condition of the previous results that the premises of the plant and the controller are synchronous. Furthermore, two crucial factors, including actuator failure and deception attacks, are taken into consideration simultaneously. Then, the mean square asymptotic stability conditions of the resultant augmented system are derived by utilizing the Lyapunov stability theory. Besides, controller gains and event-triggered parameters are co-designed with the help of linear matrix inequality techniques. Finally, a cart-damper-spring system and a nonlinear mass-spring-damper mechanical system are presented to verify the theoretical analysis.

Dynamic event-triggered output feedback control for networked Markovian jump systems under hybrid attacks

This paper investigates the dynamic event-triggered control problem for a networked Markovian jump system under hybrid attacks. In the concerned system, both the sensor-controller (S-C) network and the controller-actuator (C-A) network suffer from hybrid attacks, including denial-of-service (DoS) attacks and deception attacks. Two dynamic event-triggers at the controller and the sensor are designed to handle these dual-network hybrid attacks. Moreover, a unified framework is constructed to design an observer-based output feedback controller (OBOFC) which simultaneously considers hybrid attacks and dynamic event-triggering strategies (DETSs). Sufficient conditions to ensure the input-to-state stability (ISS) of the concerned system are derived. Furthermore, a set of linear matrix inequalities (LMIs) are proposed to obtain the desired observer-based feedback control gains and event-triggering parameters. A simulation example is given to further verify the effectiveness of the proposed control and event-triggered schemes.

Exponential stability of nonlinear systems via event-triggered impulsive control based on partial states

In the framework of partial unknown states, this paper studies the exponential stability problem of nonlinear systems. A novel event-triggered mechanism (ETM) just involving partial known states is designed to guarantee the exponential stability of considered system, where forced impulse with great freedom degree is introduced in ETM. What's more, the information of known states of the system is fetched and applied to supplement the unknown part at impulse instants. With the help of matrix analysis technique, some linear matrix inequalities (LMI) based sufficient conditions are presented from the perspective of the quantity of known and unknown states. Besides, our proposed conditions establish the relationship of event-triggered parameters, impulse interval, and impulse strength. Finally, expository examples and their numerical modeling are appeared to prove the availability of main results.