Event-triggered Transmission Scheme Research Articles

Attack-Detection-based Event-triggered Transmission Scheme for Stabilizing Cyber-Physical Systems under Denial of Service Attacks

Attack-Detection-based Event-triggered Transmission Scheme for Stabilizing Cyber-Physical Systems under Denial of Service Attacks

Event-Triggered Ultimately Bounded Filtering for Two-Dimensional Discrete-Time Systems under Hybrid Cyber Attacks

This paper investigates the design problem of event-triggered ultimately bounded filter for two-dimensional discrete systems with time-varying delays subject to hybrid cyber-attacks. A bi-directional time-sequence event-triggered transmission scheme is developed under hybrid cyber-attacks to lighten the load of network bandwidth while preserving a satisfactory filtering performance. The impact of hybrid cyber-attacks, which occur in random patterns, on the filtering performance is also taken into account. In such a framework, an augmented system model accounting for the simultaneous presence of hybrid cyber-attacks and event-triggered transmission mechanism is established with respect to two-dimensional shift-varying discrete systems with time-varying delays. On the basis of the augmented model, sufficient conditions ensuring dynamic filtering error systems exponentially ultimately bounded in the mean-square sense are obtained in virtue of Lyapunov stability theory and the linear matrix inequality technique. Then, the asymptotic upper bound of the dynamic filtering error can be specifically quantified in terms of noise variance and cyber-attacks intensity. Furthermore, criteria for simultaneously designing the weighting matrix of event-triggered scheme and the filter gain matrix are derived by minimizing the asymptotic upper bound of filtering error. Finally, the validity of proposed ultimately bounded filtering algorithm is demonstrated by utilizing an example of the industrial heating exchange process.

Improved Model-Free Adaptive Control for MIMO Nonlinear Systems With Event-Triggered Transmission Scheme and Quantization.

In this article, an improved model-free adaptive control (iMFAC) is proposed for discrete-time multi-input multioutput (MIMO) nonlinear systems with an event-triggered transmission scheme and quantization (ETQ). First, an event-triggered scheme is designed, and the structure of the uniform quantizer with an encoding-decoding mechanism is given. With the concept of partial form dynamic linearization based on event-triggered and quantization (PFDL-ETQ), a linearized data model of the MIMO nonlinear system is constructed. Then, an improved model-free adaptive controller with the ETQ process is designed. By this design, the update of the pseudo partitioned Jacobean matrix (PPJM) estimates and control inputs occurs only when the trigger conditions are met, which reduces the network transmission burden and saves the computing resources. Theoretical analysis shows that the proposed iMFAC with the ETQ process can achieve a bounded convergence of tracking error. Finally, a numerical simulation and a biaxial gantry motor contour tracking control system simulation are given to illustrate the feasibility of the proposed iMFAC method with the ETQ process.

Dissipativity-Based Consensus Tracking Control of Nonlinear Multiagent Systems With Generally Uncertain Markovian Switching Topologies and Event-Triggered Strategy.

This article focuses on the dissipativity-based consensus tracking control (DBCTC) problems of time-varying delayed leader-following nonlinear multiagent systems (LFNMASs) with the event-triggered transmission strategy. The switching topologies of the LFNMASs are subject to the uncertain and partially unknown generally Markovian jumping process. The control inputs of the following agents are updated according to the proposed event-triggered transmission strategy, which could reduce the communication burden. Based on the event-triggered transmission condition and distributed consensus protocol, some dissipativity-based criteria obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII) are proposed to guarantee the LFNMAS consensus. The validity of the main results is verified by two simulation examples.

Event-Triggered Robust Fusion Estimation for Multi-Sensor Time-Delay Systems with Packet Drops

This paper investigates the robust fusion estimation problem for multi-sensor systems with communication constraints, parameter uncertainty, d-step state delays, and deterministic control inputs. The multi-sensor system consists of a fusion center and some sensor nodes with computational capabilities, between which there are random packet drops. The state augmentation method is utilized to transform a time-delay system into a non-time-delay one. The robust state estimation algorithm is derived based on the sensitivity penalty for each sensor node to reduce the impact of modelling errors, and modelling errors here are not limited to a unique form, which implies that the fusion estimator applies to a wide range of situations. An event-triggered transmission strategy has been adopted to effectively alleviate the communication burden from the sensor node to the fusion center. Moreover, the fusion estimator handles packet drops arising from unreliable channels, and the corresponding pseudo-cross-covariance matrix is provided. Some conditions are given to ensure that the estimation error of the robust fusion estimator is uniformly bounded. Two sets of numerical simulations are provided to illustrate the effectiveness of the derived fusion estimator.

An Adaptive Event-Triggered Consensus Approach for MASs With Network-Induced Delays

This study investigates the consensus control problem of linear multi-agent systems (MASs) with network-induced delays (NIDs). A state feedback controller based on an event-triggered transmission scheme is proposed, where the novel adaptive event-triggering mechanism (ETM) is used to lower the frequency of data transmission. In contrast to previous works, sufficient conditions related to the consensus for the resulting closed-loop control systems are derived using a discontinuous looped Lyapunov functional (DLLF) and the corresponding reciprocally convex protocol. It is demonstrated that the consensus errors of resulting closed-loop control systems are asymptotically stable and the Zeno behavior is excluded. Finally, a numerical example of an unmanned aerial vehicle (UAV) model is presented to demonstrate the effectiveness of our proposed theoretical results.

Event-triggered coordinated trajectory tracking control for multiple fully-actuated MSVs under prescribed performance constraints and limited transmission resources

This paper addresses the challenging problem of event-triggered coordinated formation trajectory tracking control for multiple fully-actuated marine surface vehicles (MSVs) affected by uncertain lumped dynamics, time-varying marine environmental disturbances, and prescribed performance constraints, as well as limited transmission resources. A prescribed performance constraint is initially imposed on the neighborhood errors to overcome these issues. The radial basis function neural networks (RBF NNs) and virtual parametric method are adopted to handle the uncertain lumped dynamics and time-varying marine environmental disturbances. Meanwhile, an auxiliary dynamic system is also introduced to compensate for filtering errors. Additionally, a unique event-triggered transmission strategy is devised by innovatively constructing a lumped state term, effectively reducing the burden on the transmission network and conserving resources among the MSVs. A triggering threshold condition is constructed to ensure Zeno-free behavior in the sense that guarantees the lower bound of the release intervals is always larger than zero. The overall Lyapunov theoretical synthesis reveals the boundedness of all closed-loop signals. Finally, the effectiveness and advantages of the designed strategy for event-triggered coordinated trajectory tracking control are verified through numerical simulation.

Event-Triggered Fault Estimation and Fault Tolerance for Cyber-Physical Systems with False Data Injection Attacks

This paper investigates an event-triggered framework for addressing fault estimation and fault tolerance issues in discrete-time cyber-physical systems (CPSs) with partial state saturations and random false data injection attacks (FDIAs). A stochastic variable is introduced to characterize the random FDIAs and to establish the corresponding model. A reduced-order fault estimator and an event condition are co-derived to reconstruct system states and actuator faults. The proposed event-triggered transmission scheme helps reduce network utilization in the sensor-to-estimator channel. A sufficient condition for the proposed event-triggered estimator is derived, which minimizes state and fault estimation errors even when the controlled plants are subject to exogenous disturbances, fault signals, and random attacks. Furthermore, a fault-tolerant compensation controller is proposed using the estimated states and faults, ensuring that the considered systems achieve mean-squared stability. Finally, a DC motor platform is developed to further demonstrate the effectiveness of the designed estimator-based fault-tolerant controller.

Adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems subject to DoS attacks

AbstractThis article investigates the problem of adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems with DoS attacks. In this article, both DoS attacks and event‐triggered transmission strategy (ETTS) are considered. The DoS attacks may disturb the event‐triggered strategy, which implies that the original inequality condition of ETTS will no longer be satisfied. Different from the traditional ETTS, the adaptive ETTS is designed to reduce bandwidth usage. Based on the adaptive ETTS and resilient controller, the sufficient condition for stochastic stability of the closed‐loop system is proposed. Then, the calculation method of controller and observer parameters is given in the form of linear matrix inequality. Finally, the proposed adaptive event‐triggered resilient controller is applied to a single‐link robot arm model, which can show effectiveness of the proposed method.

Dynamic-memory event-based asynchronous security control for T-S fuzzy singular semi-Markov jump systems against multi-cyber attacks

In this paper, the design of reliable asynchronous controller for a class of Takagi Sugeno (T-S) fuzzy singular semi-Markov jump system (SSMJS) with an dynamic-memory event-triggered (DMET) transmission scheme against multiple cyber attacks. In order to improve the reliability of data transmission, the dynamic-memory event-triggered transmission scheme is proposed. A multi-cyber attacks model is established to formulate the simultaneous occurrences of deception attacks and DoS attacks. Since the modes information can not be acquired by the actual controller in real-time, the hidden Markov model (HMM) is used to describe the asynchronous phenomenon. The asynchronous controller with partly known conditional probability is properly designed, which reduces the conservatism to some extent. According to methods of stochastic Lyapunov functional and free-weighting matrices, the criteria of exponentially admissible for closed-loop system is obtained. Based on a set of linear matrix inequalities, a unified co-design method for the asynchronous controller with partial known conditional probability under the dynamic-memory event-triggered transmission scheme is proposed. Finally, the effectiveness of the proposed method is verified by comparing DMET scheme with other triggering schemes.

Adaptive Event-Triggered [formula omitted] Control of Semi-Markov Jump Distributed Parameter Systems

This paper focuses on the problem of adaptive event-triggered L2−L∞ control for distributed parameter systems with semi-Markov jump parameters. An event-triggered transmission scheme, whose threshold function can be adaptively adjusted, is established to decrease the frequency of data transmission. Simultaneously, the utilization of limited network bandwidth resources is also improved due to plenty of “unnecessary” packets being discarded before accessing networks. Furthermore, the jumping of stochastic parameters in networks can be described by a semi-Markov jump model, in which the sojourn-time is considered subject to the Weibull distribution instead of the exponential distribution. Based on the aforesaid discussions, a mode-dependent controller is designed under an adaptive event-triggered scheme. Whereafter, some criteria are constructed based on the Lyapunov stability theory to guarantee stochastic stability and a prescribed L2−L∞ performance of the system. Ultimately, two simulation examples are provided to verify the feasibility of the proposed design approach.

Simultaneous State and Unknown Input Estimation for Complex Networks With Redundant Channels Under Dynamic Event-Triggered Mechanisms.

This article addresses the simultaneous state and unknown input estimation problem for a class of discrete time-varying complex networks (CNs) under redundant channels and dynamic event-triggered mechanisms (ETMs). The redundant channels, modeled by an array of mutually independent Bernoulli distributed stochastic variables, are exploited to enhance transmission reliability. For energy-saving purposes, a dynamic event-triggered transmission scheme is enforced to ensure that every sensor node sends its measurement to the corresponding estimator only when a certain condition holds. The primary objective of the investigation carried out is to construct a recursive estimator for both the state and the unknown input such that certain upper bounds on the estimation error covariances are first guaranteed and then minimized at each time instant in the presence of dynamic event-triggered strategies and redundant channels. By solving two series of recursive difference equations, the desired estimator gains are computed. Finally, an illustrative example is presented to show the usefulness of the developed estimator design method.

Asynchronous dissipative control for networked time-delay Markov jump systems with event-triggered scheme and packet dropouts

This paper is concerned with asynchronous dissipative control for a class of networked time-delay Markov jump systems with event-triggered scheme and packet dropouts. To reduce communication consumption, an event-triggered transmission scheme is introduced. The phenomenon of packet dropout during the communication between the controller and the actuator is described by the Bernoulli model. The designed dissipative controller is asynchronous with the physical plant, which is described by a hidden Markov model. Based on a mode-dependent Lyapunov–Krasovskii function, a sufficient condition for the closed-loop control system to be stochastically stable and strictly (mu ,vartheta ,upsilon ){-}gamma-dissipative is obtained. Furthermore, the design of dissipative controller is simplified by using matrix scaling and slack matrix techniques. Finally, a robotic arm system is used as an example to verify the effectiveness of our proposed design method.

Adaptive Event-Triggered Decentralized Dynamic Output Feedback Control for Load Frequency Regulation of Power Systems With Communication Delays

In order to ensure that the power system frequency and tie-line power remain at the nominal value when the load fluctuates, while reducing the release number of decentralized sensor, this work presents a novel adaptive event-triggered scheme for the load frequency regulation via designing the decentralized dynamic output feedback controller (DOFC), where the communication delay issue is also considered due to communication constraints. Distinct from the existing ones, the proposed adaptive event-triggered strategy automatically tunes the threshold according to the local extremum of the system output signal, which can significantly reduce the number of unnecessary signal transmissions to ensure system performance. First, the proposed adaptive event-triggered transmission scheme is integrated with the decentralized DOFC and communication delays under the framework of a linear time-delay system. Then, the asymptotic stability of the closed-loop power system is analyzed through the Lyapunov stability theory and a procedure is given for the design of decentralized dynamic output load frequency controllers by solving some linear matrix inequalities (LMIs). Finally, a three-area power system is used to verify the effectiveness and usefulness of the proposed results.

Dynamic-memory event-based asynchronous dissipative filtering for T-S fuzzy singular semi-Markov jump systems against multi-cyber attacks

The paper addresses the asynchronous dissipative filter design for a class of Takagi–Sugeno (T-S) fuzzy singular semi-Markov jump systems (SSMJSs) with a dynamic-memory event-triggered (DMET) transmission scheme under multiple cyber attacks. Firstly, a dynamic-memory event-triggered scheme is introduced to improve transient performance and reduce communication burden. Meanwhile, a multiple cyber attack model considering both DoS attacks and deception attacks is constructed. Moreover, a hidden Markov model (HMM) based on the asynchronous phenomenon between the original system and the filter is established. By constructing an asynchronous dissipative filter based on HMM, the filtering error systems are transformed into SSMJSs with partially known conditional probability. Criteria of exponentially admissible and dissipative for the filtering error systems are presented concerning a set of linear matrix inequalities (LMIs). Then, based on the LMI technique, the design of the asynchronous dissipative filter and the dynamic-memory event-triggered scheme are given in a unified way. Lastly, a numerical example and a tunnel diode circuit system are given to verify the effectiveness of the theoretical results.

Event-triggered asynchronous control for switched T-S fuzzy systems based on looped functionals

In this paper, we address the event-triggered H∞ control for switched T-S fuzzy systems with asynchronism by means of looped functional approach. Different from the traditional Lyapunov functional, looped functional does not require positive definiteness and involve more sampling information, which can greatly reduce conservatism. First, we propose a mode-dependent event-triggered transmission strategy based on nonuniform sampled data. Since the switching of the system during the triggering interval will cause asynchronism, we consider the mismatch of modes and premise variables between the fuzzy system and controller. Then, by constructing appropriate two-side looped functionals including the state information of x(tk) to x(t) and x(t) to x(tk+1), several improved stability criteria are deduced for asynchronously switched T-S fuzzy systems with non-weighted L2 gain. Furthermore, fuzzy controllers and the event-triggered scheme are co-designed to guarantee the stability of the closed-loop system with a prescribed performance index. Finally, two illustrate examples with some comparison results are given to corroborate the validity and advantages of our proposed method.

Event-Triggered Bipartite Consensus for Fuzzy Multiagent Systems Under Markovian Switching Signed Topology

In this article, we study the problems of bipartite and cooperative consensus with a strictly dissipative performance for fuzzy multiagent systems (MASs) in a unified framework. First, we prove that bipartite consensus over a structurally balanced signed graph is equivalent to cooperative consensus over the corresponding unsigned graph by leveraging the gauge transformation for a class of nonlinear MASs. Then, a polynomial fuzzy model is constructed to describe the nonlinear MAS formed by one leader and followers. For mitigating communication and computational load, a mode-dependent event-triggered transmission strategy is proposed. By establishing the switching topologies through Markovian process, a new sampled-data event-triggered consensus protocol is designed. With a mode-dependent Lyapunov–Krasovskii function, a novel relaxed dissipative criterion is obtained. The criterion guarantees that all agents can achieve both event-triggered cooperative consensus and event-triggered bipartite consensus with the same magnitude but opposite signs for MASs over structurally balanced signed directed graphs and Markovian switching topologies. Moreover, the event-triggered parameters and consensus control gains can be numerically solved via the sum-of-squares method. Simulation results are given to show the effectiveness of the proposed design method.

Asynchronous filtering for Markov jump systems within finite time: A general event-triggered communication

In this paper, an event-based asynchronous H∞ filter design method for Markov jump systems over a finite-time interval is proposed. First, the hidden Markov model with a known conditional probability matrix is introduced to describe the asynchronous phenomena due to the failure of precisely obtaining the system mode information. Accordingly, an asynchronous event-triggered transmission strategy with a general threshold is presented to availably save the communication costs. Then, via using the mode-dependent Lyapunov function, a full-order filter regulated by the event-triggered strategy is established to track the system outputs. Based on Finsler’s lemma, sufficient conditions with less conservatism are deduced such that the resulting system is stochastically finite-time bounded while satisfying prescribed H∞ performance. Finally, a simulation example is implemented to illustrate the effectiveness of the theoretical results.

Dual-channel event-triggered control for positive nonlinear systems

This paper focuses on the problem of dual-channel event-triggered control for positive nonlinear systems. A dual-channel event-triggered transmission scheme is proposed to determine whether the data packets should be released or not. Two 1-norm-based event-trigger conditions are designed for the sensor-controller channel and controller-actuator channel, respectively. The condition of the system remaining positivity with the designed event-trigger conditions and feedback control law is provided. By using the Lyapunov method and matrix decomposition technique, a sufficient criterion ensuring the closed loop system to be asymptotically stable is proposed. For the linearisation purpose, the control gain is delicately decomposed into a nonnegative component and a non-positive component. Zeno behaviour of the designed event-triggered transmission of sampled data packets is further rigorously proved to be excluded. An example of water pollution control system is provided to show the effectiveness of the obtained results.

Finite-time event-triggered filtering of the discrete-time switched linear systems with time delay

The finite-time event-triggered filtering of the discrete-time switched linear systems with time delay is addressed in the paper. The switched system and its filtering switched system are established as a filtering error system (FES) with augmented switching signal by the merging switching signal technique. The asynchronous switching phenomenon of switched system modes and filter modes occurs since a mode-dependent event-triggered transmission scheme (METS) which determines the system output and switching signal is addressed. Meanwhile, by the average dwell time (ADT) and multi-Lyapunov functional method, some sufficient conditions are given to make certain that the FES is finite-time bounded (FTB) and has a specified performance. Furthermore, the finite-time filter is designed by solving linear matrix inequalities. Ultimately, a numerical example is inspired to manifest the availability of the effects in the study.