Event-triggered Control Approach Research Articles

Fuzzy control for networked systems with mixed data missing under quantization based event-triggered scheme

This paper presents an innovative event-triggered fuzzy control approach for networked systems operating over unreliable network channels. Traditional complicated modeling and analysis process of network induced issues is replaced by a bran-new logarithmic quantization based event-triggered scheme method. The joint characterization of mixed data missing, arising from the event-triggered mechanism and unreliable network channels, becomes a challenging issue due to disrupted data sequences and variable relations. Consequently, this paper contributes a formulated auxiliary stochastic sequence approach to overcome the difficulty of dynamics modeling. With an formulated event driven controller, the modeling and implementation of the closed-loop systems are constructed and further simplified. Considering the difference and relation between the membership functions of plant and controller, we present a new fuzzy output feedback controller design method to obtain feasible result via uncertainty based method. Finally, we verify the validity of the designed control policy via a simulation example.

Synchronization of Fractional Stochastic Neural Networks: An Event Triggered Control Approach

Synchronization of Fractional Stochastic Neural Networks: An Event Triggered Control Approach

Matrix Measure-Based Event-Triggered Impulsive Quasi-Synchronization on Coupled Neural Networks.

In this article, the quasi-synchronization for a kind of coupled neural networks with time-varying delays is investigated via a novel event-triggered impulsive control approach. In view of the randomly occurring uncertainties (ROUs) in the communication channels, the global quasi-synchronization for the coupled neural networks within a given error bound is considered instead of discussing the complete synchronization. A kind of distributed event-triggered impulsive controllers is presented with considering the Bernoulli stochastic variables based on ROUs, which works at each event-triggered impulsive instant. According to the matrix measure method and the Lyapunov stability theorem, several sufficient conditions for the realization of the quasi-synchronization are successfully derived. Combining with the mathematical methodology with the formula of variation of parameters and the comparison principle for the impulsive systems with time-varying delays, the convergence rate and the synchronization error bound are precisely estimated. Meanwhile, the Zeno behaviors could be eliminated in the coupled neural network with the proposed event-triggered function. Finally, a numerical example is presented to prove the results of theoretical analysis.

Event-triggered impulsive control for second-order nonlinear multi-agent systems under DoS attacks

<abstract><p>We investigated impulsive consensus in second-order nonlinear multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. We consided scenarios where the communication network is subjected to DoS attacks, disrupting communication links and causing changes in the communication topology. An event-triggered impulsive control(ETIC) approach is proposed to flexibly address these issues. Additionally, an upper bound on the DoS attack period is introduced. Finally, a numerical example is given to verify the validity of the major results.</p></abstract>

A Novel Adaptive Event-Triggered Consensus Control Approach to Multi-Agent Systems With Guaranteed Positive MIET

A Novel Adaptive Event-Triggered Consensus Control Approach to Multi-Agent Systems With Guaranteed Positive MIET

Observer-based dynamic event-triggered adaptive control for uncertain nonlinear strict-feedback systems

This paper proposes an observer-based dynamic event-triggered adaptive control approach for uncertain nonlinear strict-feedback systems. Initially, an observer for unmeasurable states is constructed. Subsequently, employing backstepping technique, the output-feedback adaptive control law and parameter adaptive law are developed. The tuning function method is used to avoid the over-parameterization problem in parameter adaptive law design. To lower the data exchange rate within the network, a dynamic event-triggered scheme is formulated to allow real-time update control signal. Through Lyapunov theory analysis, the resulting closed-loop system is demonstrated to be stabilized, and the occurrence of Zeno behavior is effectively prevented. Finally, the simulation example validates the obtained result of the presented design approach.

Event-Triggered Path Following Robust Control of Underactuated Unmanned Surface Vehicles with Unknown Model Nonlinearity and Disturbances

An effective path-following controller is a guarantee for stable sailing of underactuated unmanned surface vehicles (USVs). This paper proposes an event-triggered robust control approach considering an unknown model nonlinearity, external disturbance, and event-triggered mechanism. The proposed method consists of guidance and dynamic control subsystems. Based on the tracking error dynamics equations, the guidance subsystem is designed to achieve the guidance law. For the dynamic control subsystem, the radial basis function neural networks (RBFNNs) are designed to approximate the unknown model nonlinearity and external disturbances to improve the robustness of the proposed method. In addition, an event-triggered mechanism is constructed to reduce the triggering times. The closed-loop system is proven to be stable, and the effectiveness of the proposed method is illustrated through simulation results.

Model-based event-triggered control for linear systems using a finite-time convergent observer

In this paper, we present an improved model-based event-triggered control approach for regulation of networked linear time-invariant plants by integrating a finite-time convergent observer. Utilizing the send-on-delta concept, we introduce two event-triggering strategies that substantially decrease the number of samples transmitted over the sensor-to-controller communication channel: (1) one strategy guarantees global asymptotic stability of a tunable compact neighborhood of the origin with a finite number of sampling events; (2) the other strategy ensures global asymptotic stability of the origin with arbitrarily large inter-sampling time. Through the lens of hybrid systems theory, we demonstrate that both methods avoid Zeno solutions, making them suitable for digital implementation, and both strategies exhibit robustness against both small and large perturbations. We showcase the advantages of our proposed strategies over other model-based approaches using a perturbed linearized batch reactor example.

Robust Output Regulation of Linear Uncertain Systems by Dynamic Event-Triggered Output Feedback Control.

In this article, the robust output regulation problem of the linear uncertain system is investigated by the event-triggered control approach. Recently, the same problem is addressed by an event-triggered control law where the Zeno behavior may happen when time tends to infinity. In comparison, a class of event-triggered control laws is developed to achieve output regulation exactly, and meanwhile, explicitly exclude the Zeno behavior for all time. In particular, a dynamic triggering mechanism is first developed by introducing a dynamic changing variable with specific dynamics. Then, by the internal model principle, a class of dynamic output feedback control laws is designed. Later, a rigorous proof is provided to show that the tracking error of the system converges to zero asymptotically while prohibiting the Zeno behavior for all time. Finally, we give an example to illustrate our control approach.

Output synchronization of wide-area multi-agent systems via an event-triggered hybrid control approach

This study considers an output synchronization problem for a clustered multiagent system (CMAS) in a wide-area communication network. Motivated by energy and communication constraints, a wide-area communication network was modeled via a directed graph consisting of clusters, each having a spanning tree with a leader as the root. To avoid continuous updates to the controller, the communications among agents inside each cluster were implemented in an event-triggered manner, and inter-cluster communications were executed by leaders only at the event-triggered time instants. Hybrid reduced-order observers were designed for agents and leaders when only output information was available. To drive all agents to achieve output synchronization, a hybrid event-triggered control strategy was then suggested to each agent. Several sufficient conditions were obtained using the Lyapunov function method for analyzing stability of the hybrid closed-loop CMASs. Simultaneously, any manifestation of Zeno behavior was analyzed and simulation results were shown to illustrate the feasibility of the proposed event-triggered hybrid control strategy.

Periodic Event-Triggered CACC and Communication Co-design for Vehicle Platooning

Cooperative Adaptive Cruise Control (CACC) based vehicle platooning can increase the safety and efficiency of traffic. This work looks into the communication and control problems of vehicle platooning, and proposes a control and communication co-design for CACC. First, an integrated radar system is presented. This system integrates sensing of relative position, speed, and communication between a predecessor and its follower. Second, a working scheme for the integrated radar system is presented. This scheme allows the radar systems to switch periodically between different working modes without interferences from other modes. Therefore, the relative position, speed, and communication can be asynchronously periodically updated to the controller. Third, a periodic event-triggered control approach is presented. This approach allows asynchronous periodic sampling of the output, and is deeply co-designed with the radar system and its working scheme. Delays are also considered in the control approach. The co-design CACC approach can guarantee the vehicle platoons to be string stable. A numerical example has shown the feasibility of the approach.

A fully distributed event-Triggered control approach to leader-following consensus of multiagent systems

This paper investigates the leader-following consensus problem for general linear multiagent systems under a fully distributed manner. To avoid using the global information of the communication network, two node-based adaptive parameters are designed and introduced to the fully distributed event-based control law. Such a protocol is more scalable and flexible for large-scaled and complex networked system, such as microgrids or multiple unmanned vehicles. A novel event-triggered rule is presented, and an internal dynamic variable is introduced in it to further cut down the triggering times and save the communication resources. A well-designed Lyapunov function candidate is constructed to not only ensure the convergence of the close-looped systems but also avoid using the eigenvalue of Laplacian matrix in the dynamic variable. Moreover, it is proved that the designed event-triggered conditions can avoid the Zeno behaviour. Finally, a simulation example based on a group of unmanned intelligent vehicle systems is provided to demonstrate the validity of the designed control method.

Event-triggered finite-time fuzzy control approach for fractional-order nonlinear chaotic systems with input delay

In this paper, a novel fuzzy event-triggered control approach with guaranteed performance of practical finite-time tracking convergence is constructed for uncertain fractional-order nonlinear chaotic systems in the presence of time-varying input delay. Firstly, fuzzy logic systems are employed to deal with immeasurable systematic information. Secondly, fractional-order command filters are incorporated to circumvent the problem of “complexity explosion” in backstepping controller construction. Meanwhile, a sequence of fractional-order finite-time compensation signals are introduced to counteract the adverse influence of time-varying input delay rapidly. Furthermore, a novel practical finite-time chaos control approach based on event-triggered strategy is proposed, which not only facilitates the decrease of sampling frequency and controller burden dynamically, but also ensures the convergence of all tracking errors towards a small region around the origin in finite time. Finally, through the simulation research, the transient response performance and the chaos-suppression ability of fractional-order chaotic systems stabilized via the suggested approach are rigorously testified.

Distributed Event-Triggered Control of DC Microgrids With Input Saturation and Time Delay Constraints

This article proposes a novel distributed event-triggered secondary control approach subject to input saturation and time delay in communication links among distributed generators (DGs) to achieve both voltage restoration and proportional current sharing in islanded DC microgrids (MGs). In contrast to periodic communication, sampled-data exchanges only occur when the triggering condition is satisfied. Therefore, communication instants and computation burdens will be reduced significantly. Compared with the existing event-triggered mechanism, this article investigates conditions for achieving consensus in the presence of both input saturation and time delay constraints. The Lyapunov synthesis is employed to derive the stability and convergence analysis of the proposed event-triggering condition and ensure the Zeno-free of the system. Finally, the effectiveness of the proposed controller is validated by simulating its performance under various scenarios in an islanded DC MG using the MATLAB/SimPowerSystems Toolbox.

A hybrid event-triggered stabilization approach for switched systems under asynchronous switching and its application

This paper investigates the stabilization problem of switched systems with mismatched modes by an event-triggered control approach. A hybrid event-triggered scheme (HETS) with a dynamically adjustable threshold is newly proposed, which combines periodic sampling, continuous event-trigger and slow switching. It is assumed that the modes and states of the controller are updated only at each triggering instant, so the situation of asynchronous switching could arise. Compared with the control strategy under static HETS, the proposed hybrid event-triggered control strategy has the advantage of potentially speeding up the stabilization while reducing the communication burden. To ease the analysis, the closed-loop system is accordingly represented as a combination of the switched system with a periodically sampled control input and the one with a continuously event-triggered control input. By considering input delay information in the construction of multiple Lyapunov–Krasovskii functional (LKF), a discontinuous and non-positive definite LKF is developed to establish sufficient conditions on the exponential stability for the closed-loop switched system. The design method of the desired controller and HETS is then provided. Finally, the result obtained in this paper is applied to a networked continuous stirred tank reactors system.

Distributed dynamic event‐triggered control for resilience‐oriented current sharing in microgrid

AbstractDistributed dynamic event‐triggered control (ETC) method is proposed to solve the stochastic and intermittent problem caused by distributed renewable energy generation unit (DG) in microgrid (MG). It aims at reducing communication cost while achieving proportional current sharing among DGs. Firstly, the state space function model of the MG system is established, considering the unknown disturbance caused by DGs and the uncertainty caused by the constant power load (CPL). Also, the system model is transformed into the standard linear heterogeneous multiagent systems (LHMAS). Subsequently, the distributed dynamic ETC method with consensus algorithm is proposed to achieve proportional current sharing among DGs. Compared with conventional ETC approaches, the authors’ method is based on directed topology, which reduces the controller updating frequency and the communication frequency among DGs. At the same time, the Zeno behaviour can be avoided. Additionally, the authors’ method is much easier to be implemented, which can also handle the uncertain loads and CPLs. Finally, the simulation results demonstrate the effectiveness of the proposed method.

Adaptive Event-Triggered Control Approach to the Cooperative Output Regulation of Heterogeneous Multiagent Systems Under Digraphs

The cooperative output regulation (COR) problem of heterogeneous linear multiagent systems under digraphs has been considered under the assumption that continuous communication between neighbors and continuous update of controllers. To get rid of this assumption, that is, to realize event-triggered communication between neighbors and discrete update of controllers, this article proposes the fully distributed event-triggered observers to estimate the matrix and the state for the exosystem, and the event-triggered controllers to solve the COR problem. Moreover, the Zeno behavior is excluded by proving that the interevent times of each agent are strictly greater than zero under the design triggering conditions. Finally, two examples are given to verify the effectiveness and advantages of the proposed methods.

Event-triggered adaptive optimal tracking control for nonlinear stochastic systems with dynamic state constraints

This paper investigates the issue of event-triggered adaptive optimal tracking control for uncertain nonlinear systems with stochastic disturbances and dynamic state constraints. To handle the dynamic state constraints, a novel unified tangent-type nonlinear mapping function is proposed. A neural networks (NNs)-based identifier is designed to cope with the stochastic disturbances. By utilizing adaptive dynamic programming (ADP) of identifier-actor-critic architecture and event triggering mechanism, the adaptive optimized event-triggered control (ETC) approach for the nonlinear stochastic system is first proposed. It is proven that the designed optimized ETC approach guarantees the robustness of the stochastic systems and the semi-globally uniformly ultimately bounded in the mean square of the NNs adaptive estimation error, and the Zeno behavior can be avoided. Simulations are offered to illustrate the effectiveness of the proposed control approach.

Event-Triggered Robust Adaptive Dynamic Programming With Output Feedback for Large-Scale Systems

In this article, an event-triggered output-feedback adaptive optimal control approach is proposed for large-scale systems with parametric and dynamic uncertainties through robust adaptive dynamic programming and small-gain techniques. By using the input and output data, the unmeasurable states are reconstructed instead of designing a Luenberger observer. To save the communication resources and reduce the number of control updates, an event-based feedback control policy is learned based on policy iteration and value iteration, respectively. The closed-loop stability and the convergence of the proposed algorithms are analyzed by using Lyapunov stability theory and small-gain techniques. A practical example of multimachine power systems with governor controllers is given to demonstrate the effectiveness of the proposed methods.

Event-Triggered Model Reference Adaptive Control for Linear Partially Time-Variant Continuous-Time Systems With Nonlinear Parametric Uncertainty

In this work, we develop an event-triggered adaptive control approach for solving the state tracking problem of linear partially time-variant continuous-time systems with the nonlinear state-dependent matched parametric uncertainty under unknown system dynamics. First, an event-triggered model reference adaptive controller is designed, which is composed of event-triggered adaptive laws based on the event-updated information and an event-triggering condition depending on the state tracking error of the controlled plant and reference model. Then, the state-tracking error and the error between control parameters and ideal ones of the resulting closed-loop system are proven to be uniformly ultimately bounded. Moreover, based on the designed event-triggering condition, the interevent time between two consecutive triggering points is proven to have a positive lower bound. Finally, a simulation example is provided to show the effectiveness of the proposed approach.