Event-triggered Communication Protocol Research Articles

Event-triggered filtering for complex networks subject to random coupling strength and missing measurements: A partial-nodes accessible case

In this paper, the event-triggered filtering issue is addressed for a class of discrete-time nonlinear complex networks (CNs) considering random coupling strength (RCS) and missing measurements (MMs) under the condition that partial nodes information is accessible. To begin with, a uniformly distributed random variable over a settled interval is employed to model random changes in coupling strength. Then, a Bernoulli distributed random variable is considered to depict the phenomenon of MMs with uncertain occurrence probability. The event-triggered communication (ETC) protocol is applied to schedule data to relieve transmission burden. Subsequently, a novel partial-node-based recursive filtering algorithm is constructed by taking the influence of RCS, MMs and ETC mechanism into account, in which the filter gain is parameterized to achieve the minimization for the upper bound of filtering error covariance (UBFEC). Besides, performance discussion for the developed filter is provided through strict theoretical derivations, including the uniform boundedness and monotonicity relationship. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed estimation scheme.

Distributed formation tracking for multi-UAVs with unknown disturbances under event-triggered communication

This paper presents a novel distributed formation control scheme under event-triggered communication to solve the cooperative formation tracking problem of multiple unmanned aerial vehicles (multi-UAVs) with unknown disturbances. An event-triggered communication protocol whose triggering condition depends on the system’s current state is designed, and thus reduces the unnecessary communication consumption. Based on such communication protocol, a robust formation control is constructed and skillfully combined with disturbance estimator to further enhance the robustness to resist unknown disturbances. Moreover, an event-triggered strategy is further incorporated to update the controller. By employing Lyapunov theory, new sufficient conditions for guaranteeing the system’s stability are rigorously derived, while excluding Zeno behavior. The efficiency and advantage of our method are illustrated by numerical validation of formation tracking under unknown nonlinear disturbances and detailed comparisons with closely related works. Our method is also verified in an ROS/PX4/Gazebo platform, fully indicating its significant value for applications.

Optimal leader-following consensus under switching topologies based on event-triggered NN-based observer

This paper proposes a novel control strategy for multi-agent systems (MASs) to achieve optimal leader-following consensus under jointly connected topologies. The devised approach incorporates two key components: an event-triggered neural network (NN)-based leader observer and an NN-based optimal controller. The proposed leader observer allows followers to locally reconstruct the leader’s dynamics, even in scenarios where the communication topology is jointly connected. The implementation of an event-triggered communication protocol significantly reduces the communication burden, enhancing the overall efficiency of information exchange. As the observer’s state converges to the actual leader’s state, the simplification of achieving leader-follower consensus becomes evident by directly setting the state of the leader observer as the tracking goal. An NN-based optimal controller is utilized to approximate the solution to the Hamilton–Jacobi–Bellman (HJB) equation, thus enabling optimal tracking of the leader by followers. Finally, the performance of the proposed control strategy is verified by simulations.

Sliding-Mode Control for IT2 Fuzzy Nonlinear Singularly Perturbed Systems and Its Application to Electric Circuits: A Dynamic Event-Triggered Mechanism

This work is devoted to an <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> sliding-mode control for nonlinear singularly perturbed system under a network control framework. Aiming at describing the nonlinearities with parameter uncertainties in the studied system, the idea of interval type-2 (IT2) fuzzy method is employed in the system modeling. A disturbance observer is developed to acquire the unknown disturbance, and the estimated value is implemented into the controller for neutralizing the influence of the disturbance. To further reduce the occupation of network resources, an event-triggered communication protocol with a dynamic threshold parameter is adopted, where the triggered condition can be adjusted adaptively as the evolution of the system states. Then, an appropriate fuzzy integral sliding motion is constructed based on the constructed system model and disturbance estimation. It is worth noting that the constructed fuzzy controller follows the idea of nonparallel distribution compensation, which improves the designed flexibility. In terms of fuzzy processing, by introducing the membership functions dependent method into the stability analysis, a series of relaxed criteria are established to ensure the global asymptotic stability for the closed-loop systems with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty}$</tex-math> </inline-formula> performance level. Finally, two classical examples of circuit model and inverted pendulum model are extended to IT2 fuzzy idea, showing the rationality of the proposed approach.

Novel Extended State Observer Design for Uncertain Nonlinear Systems via Refined Dynamic Event-Triggered Communication Protocol.

In this article, an extended state observer (ESO) design problem is investigated for uncertain nonlinear systems subject to limited network bandwidth. First, for rational information exchange scheduling, a dynamic event-triggered (DET) communication protocol is proposed. Different from the traditional static event-triggered strategies with fixed thresholds, an internal dynamic variable is introduced to be adaptively adjusted by a dual-directional regulating mechanism. Thus, more desirable tradeoff between observation performance and communication resource efficiency is achieved. Second, inspired by our early work on Takagi-Sugeno fuzzy ESO (TSFESO), a novel paradigm of event-triggered TSFESO is initially proposed. Third, under the DET mechanism, the TSFESO design approach is derived to carry out exponential convergence for estimation error dynamics. Finally, the effectiveness of the proposed method is verified by numerical examples. The nonlinear estimating efficiency and linear numerical tractability are integrated in TSFESO. In addition, a generalized ESO formulation is developed to allow some nonadditive uncertainties incompatible with total disturbance, such as improved event-triggered strategy, and thus, the application sphere of ESO is further expanded.

Event-triggered [formula omitted] leader-follower consensus for nonlinear multi-agent systems with fixed and switching network topologies

This paper investigates H∞ leader-follower consensus problems of nonlinear multi-agent systems via event-triggered control. To significantly reduce the communication burdens, a distributed estimator-based event-triggered communication protocol is proposed. By using Lyapunov stability theory, matrix theory and algebraic graph theory, we derive some sufficient conditions to guarantee the leader-follower consensus with desired H∞ performance. Distributed triggering functions are designed for three cases: fixed topologies, switching topologies with connected sub-topologies and frequently connected switching topologies. Furthermore, we prove that the Zeno-behavior can be excluded for three cases, respectively. Finally, simulations are presented to illustrate the effectiveness of the theoretical results.

A Dynamic Event-Triggered Approach to Recursive Nonfragile Filtering for Complex Networks With Sensor Saturations and Switching Topologies.

In this article, the nonfragile filtering issue is addressed for complex networks (CNs) with switching topologies, sensor saturations, and dynamic event-triggered communication protocol (DECP). Random variables obeying the Bernoulli distribution are utilized in characterizing the phenomena of switching topologies and stochastic gain variations. By introducing an auxiliary offset variable in the event-triggered condition, the DECP is adopted to reduce transmission frequency. The goal of this article is to develop a nonfragile filter framework for the considered CNs such that the upper bounds on the filtering error covariances are ensured. By the virtue of mathematical induction, gain parameters are explicitly derived via minimizing such upper bounds. Moreover, a new method of analyzing the boundedness of a given positive-definite matrix is presented to overcome the challenges resulting from the coupled interconnected nodes, and sufficient conditions are established to guarantee the mean-square boundedness of filtering errors. Finally, simulations are given to prove the usefulness of our developed filtering algorithm.

Dynamic event‐triggered control for leader‐following consensus of multiagent systems with the estimator

In this paper, the leader-following consensus problem of general linear multi-agent systems with distributed dynamic event-triggered control is studied. A distributed controller with estimated states is designed and a dynamic event-triggered communication protocol with an auxiliary variable is proposed for each agent to update its triggering threshold. Under this control strategy, the systems only need the states in triggering instants as a result of the utilisation of estimated states. The existence of a dynamic threshold guarantees fewer triggering times, in contrast to the conventional static one. Meanwhile, the estimator is designed between the triggering instants to reduce the state shift, the next state of each agent depends on the local information of itself and its neighbours rather than global information. Then, the multi-agent systems can achieve consensus without Zeno behaviour. Finally, a simulation example is offered to verify the effectiveness and feasibility of the proposed approach.

Event-triggered optimal Kalman consensus filter with upper bound of error covariance

In this paper, we present an event-triggered optimal Kalman consensus filter (EOKCF) for state estimation in distributed wireless sensor networks. The local message is exchanged only when the local estimation violates a predetermined Send-on-Delta (SoD) data transmission condition in order to reduce the amount of data transfer. The neighboring measurement and estimation information are integrated into the consensus filter, and a recursive upper bound of the error covariance is derived for uncertainties of interval communication from the event-based systems. The optimal Kalman gain and consensus gain matrices are obtained by minimizing the upper bound of state error covariance. The Crameˇr−−Rao lower bound (CRLB) of the state estimates is also introduced to measure the mean-square estimation error performance. The effectiveness of event-triggered communication protocol and the advantages of filtering performance of EOKCF are demonstrated using Monte Carlo simulations on a target tracking application in a distributed sensor network.

Discrete specified time consensus control of aggregated energy storage for load frequency regulation

Small scale energy storage systems (ESSs) can serve as buffers for integrating renewable energy resources into the main grid. Their available energy can be aggregated to provide ancillary services for power systems. This paper considers a load frequency control (LFC) scheme with energy storage aggregator comprises of ESSs. To coordinate the behaviors of ESSs for LFC support, a discrete prescribed time consensus control is proposed which ensures that the ESSs can reach consensus within the prescribed settling time. To improve the tracking precision, an optimal leader set is selected with submodular optimization. In the meantime, an event triggered communication (ETC) protocol is proposed to reduce the unnecessary information sharing among ESSs. The ETC protocol is naturally Zeno free with the defined sampling instants. Case studies are conducted to validate the effectiveness of the proposed method, and the performance of the proposed method is superior than conventional and state-of-art methods with comparative studies.

Distributed Online VAR Control for Unbalanced Distribution Networks With Photovoltaic Generation

The unbalanced nature of the distribution networks (DNs) and communication asynchrony pose considerable challenges to the distributed voltage regulation. In this paper, two distributed voltage control algorithms are proposed to overcome these challenges in multiphase unbalanced DNs. The proposed algorithms can be leveraged in online implementations to cope with the fast-varying system operating conditions. By adopting the linearized multiphase DistFlow model, the voltage control problem is formulated as a convex quadratic programming problem for which a synchronous distributed algorithm is developed based on the dual ascent method. To account for communication delays, an asynchronous distributed algorithm is proposed evolving from the synchronous one by incorporating an event-triggered communication protocol. Furthermore, closed-form solutions to the optimization subproblems are derived to enhance the computational efficiency, and communication complexity is reduced significantly to the extent that only neighborhood information exchange is required. Finally, the convergence of the proposed algorithms to the global optimality is established analytically. Numerical tests on the IEEE 123-bus network not only corroborate that our proposed algorithms are more efficient in eliminating voltage violations and minimizing network loss compared with two benchmarks but also validate their effectiveness for online implementations.

Adaptive Droop Gain-Based Event-Triggered Consensus Reactive Power Sharing in Microgrids

This paper proposes an adaptive droop gain-based consensus approach for reactive power sharing in microgrids (MGs) with the event triggered communication protocol (ETCP). A multi-agent system-based network is constructed to establish the communication with distributed generators (DGs) in MGs. An ETCP is proposed to reduce the communication among agents to save resources and improve system reliability, as the communication is only needed when the event triggered condition is fulfilled. A stability analysis is conducted to guarantee the existence of the equilibrium point and the freeness of the Zeno solution. Moreover, an adaptive droop gain is designed to reduce the impact of imbalanced feeder impedances. Four case studies are conducted to verify the effectiveness and performance of the proposed method. The simulation results show that the ETCP-based approach is capable of achieving power sharing consensus, communication reduction and shifting the information exchange mode based on the operation scenarios.

Decentralized Event-Triggered Adaptive Control of Discrete-Time Nonzero-Sum Games Over Wireless Sensor-Actuator Networks With Input Constraints.

This article studies an event-triggered communication and adaptive dynamic programming (ADP) co-design control method for the multiplayer nonzero-sum (NZS) games of a class of nonlinear discrete-time wireless sensor-actuator network (WSAN) systems subject to input constraints. By virtue of the ADP algorithm, the critic and actor networks are established to attain the approximate Nash equilibrium point solution in the context of the constrained control mechanism. Simultaneously, as the sensors and actuators are physically distributed, a decentralized event-triggered communication protocol is presented, accompanied by a dead-zone operation which avoids the unnecessary events. By predefining the triggering thresholds and compensation values, a novel adaptive triggering condition is derived to guarantee the stability of the event-based closed-loop control system. Then resorting to the Lyapunov theory, the system states and the critic/actor network weight estimation errors are proven to be ultimately bounded. Moreover, an explicit analysis on the nontriviality of the interevent times is also provided. Finally, two numerical examples are conducted to validate the effectiveness of the proposed method.

Distributed prescribed performance pinning synchronization for complex dynamical networks with event-triggered communication protocols

This paper proposes a distributed synchronization strategy of complex dynamical networks with prescribed performance under pinning control, via event-triggered communication protocols. Besides guaranteeing the transient performance of synchronization process, the provided pinning control can ensure the synchronization errors converge to the origin. Moreover, a sufficient condition of the synchronization is also given on the basis of the Lyapunov stability theory. The novelties of this paper are that not only transient performance of synchronization for complex dynamical networks is guaranteed, but also continuous communication among network nodes can be avoided under event-triggered pinning control, which can decrease the number of both controlled nodes and information updates. What is more, the Zeno behavior is eliminated in communication process of the networks. At last, the validity and the effectiveness of the theoretic results obtained are verified by means of the application in the complex dynamical network with Chua’s circuit.

A Set-Membership Approach to Event-Triggered Filtering for General Nonlinear Systems Over Sensor Networks

This paper is concerned with the distributed set-membership filtering problem for a class of general discrete-time nonlinear systems under event-triggered communication protocols over sensor networks. To mitigate the communication burden, each intelligent sensing node broadcasts its measurement to the neighboring nodes only when a predetermined event-based media-access condition is satisfied. According to the interval mathematics theory, a recursive distributed set-membership scheme is designed to obtain an ellipsoid set containing the target states of interest via adequately fusing the measurements from neighboring nodes, where both the accurate estimate on Lagrange remainder and the event-based media-access condition are skillfully utilized to improve the filter performance. Furthermore, such a scheme is only dependent on neighbor information and local adjacency weights, thereby fulfilling the scalability requirement of sensor networks. In addition, an optimization algorithm is developed to minimize the trace of the estimated ellipsoid set, and the effect from the adopted event-triggered threshold is thoroughly discussed as well. Finally, a simulation example is utilized to illustrate the usefulness of the proposed distributed set-membership filtering scheme.

Distributed Kalman Filters With State Equality Constraints: Time-Based and Event-Triggered Communications

In this paper, we investigate a distributed estimation problem for multi-agent systems with state equality constraints (SEC). First, under a time-based consensus communication protocol, applying a modified projection operator and the covariance intersection fusion method, we propose a distributed Kalman filter with guaranteed consistency and satisfied SEC. Furthermore, we establish the relationship between consensus step, SEC and estimation error covariance in dynamic and steady processes, respectively. Employing a space decomposition method, we show the error covariance in the constraint set can be arbitrarily small by setting a sufficiently large consensus step. Besides, we propose an extended collective observability (ECO) condition based on SEC, which is milder than existing observability conditions. Under the ECO condition, through utilizing a technique of matrix approximation, we prove the boundedness of error covariance and the exponentially asymptotic unbiasedness of state estimate, respectively. Moreover, under the ECO condition for linear time-invariant systems with SEC, we provide a novel event-triggered communication protocol by employing the consistency, and give an offline design principle of triggering thresholds with guaranteed boundedness of error covariance. More importantly, we quantify and analyze the communication rate for the proposed event-triggered distributed Kalman filter, and provide optimization based methods to obtain the minimal (maximal) successive non-triggering (triggering) times. Two simulations are provided to demonstrate the developed theoretical results and the effectiveness of the filters.

Event-Triggered Control for Consensus of Multiagent Systems With Fixed/Switching Topologies

In this paper, the leader-following consensus problem of high-order multiagent systems via event-triggered control is discussed. A novel distributed event-triggered communication protocol based on state estimates of neighboring agents is proposed to solve the consensus problem of the leader-following systems. We first investigate the consensus problem in a fixed topology, and then extend to the switching topologies. State estimates in fixed topology are only updated when the trigger condition is satisfied. However, state estimates in switching topologies are renewed with two cases: 1) the communication topology is switched or 2) the trigger condition is satisfied. Clearly, compared to continuous-time interaction, this protocol can greatly reduce the communication load of multiagent networks. Besides, the event-triggering function is constructed based on the local information and a new event-triggered rule is given. Moreover, “Zeno behavior” can be excluded. Finally, we give two examples to validate the feasibility and efficiency of our approach.

Non-fragile – control for discrete-time stochastic nonlinear systems under event-triggered protocols

In this paper, the non-fragile – control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the – performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the – performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.

Synchronization of Multiagent Systems Using Event-Triggered and Self-Triggered Broadcasts

This paper addresses the problem of synchronizing a group of identical linear time-invariant agents that exchange information through a communication network. The agents may only broadcast information at discrete-time instants and the decision to execute a broadcast is based on an event-triggered communication protocol. We prove that with the proposed control architecture the state of each agent converges to and remains in a neighborhood of a desired reference signal and the closed-loop system does not exhibit Zeno solutions. A self-triggered implementation of the proposed event-triggered communication protocol is also derived.

Event‐triggered Kalman consensus filter over sensor networks

Kalman consensus filter (KCF) has been developed for distributed state estimation over sensor networks where local estimates are exchanged with time-triggered transmission mechanism. To reduce the amount of data transfer in sensor networks, the authors propose a KCF with an event-triggered communication protocol. The triggering decision is based on the send-on-delta data transmission mechanism: each sensor transmits its local estimates to its neighbours only if the difference between the most recent transmitted estimate and the current estimate exceeds a tolerable threshold. On the basis of the event-triggered communication protocol, an optimal Kalman gain matrix is derived by minimising the mean squared errors for each sensor and a suboptimal KCF is developed for scalable considerations. By using the Lyapunov-based approach, a sufficient condition is presented for ensuring the stochastic stability of the suboptimal KCF. A numerical example is provided to verify the effectiveness of the proposed filter.