Event-triggered Approach Research Articles

Robust Stability of Networked Linear Control Systems With Asynchronous Continuous- and Discrete-Time Event-Triggering Schemes

This article presents a unified framework for the stability and performance analysis of networked linear control systems with asynchronous continuous-time or discrete-time event-triggering. In the networked system, the multiple outputs of the plant and the controller are independently transmitted via a single shared or multiple channels based on local event-triggering conditions. Regarding the restrictions of physical devices, in the event-checking procedure, an inactive period of time is allowed after each event of data sending. So the Zeno behaviors in events are effectively avoided. In terms of algebraic properties of state-space models and time delays, we present sufficient conditions for asymptotic stability and guaranteed L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> gain performance and characterize the robustness of the system in a time-delayed networked scenario with independent event-triggered sending of each output. The event-triggered approach provides the potential benefit of reduced number of requests for sending data via networks. A simulation example is given to verify the proposed methods.

Secure Control of Networked Switched Systems with Random DoS Attacks via Event-triggered Approach

This paper considers security control of networked switched systems in which the denial-of-service attacks may happen when the output information is transmitted from the sensor to the controller. Besides, it is assumed that the denial-of-service obeys Bernoulli distribution. First, to reduce the communication burden and retaining a satisfactory performance, an event-triggered sampling mechanism is adopted. And then, security control of the switched systems is analyzed by designing an output-feedback controller and a switching signal based on the average dwell time method. It is shown that the state trajectory can be driven onto a certain bound despite the presence of the random denial-of-service attacks. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.

Event-based Finite-time Boundedness of Discrete-time Network Systems

This paper deals with the event-based finite-time H∞ control problem of discrete-time network control systems with norm bounded input disturbances and nonlinear stochastic functions. A network-induced delay stochastic model is first constructed by event-triggered approach. Utilizing stochastic analysis and event-triggered schemes, conditions on stochastic finite-time (FT) boundedness and stochastic H∞ FT boundedness are then derived for the network model. Subsequently, an event-based finite-time controller and an event-triggered matrix are co-designed to ensure that the stochastic model is stochastically FT bounded or stochastically H∞ FT bounded by utilizing matrix decomposition scheme. All derived criteria can be solved in terms of convex optimal method, and numerical examples demonstrate the validity of obtained results as well.

A Hybrid Event-Triggered Approach to Consensus of Multiagent Systems With Disturbances

This article investigates the event-triggered consensus problem for multiagent systems (MAS) with external disturbances. A hybrid event-triggering mechanism (ETM) is proposed, which utilizes time regularization to force the minimum interevent time to be strictly positive, such that Zeno freeness is ensured in the presence of disturbances. Model-based control protocol is used to avoid continuous communication between neighboring agents. With the proposed hybrid ETM, the closed-loop MAS contains both flow dynamics and jumping dynamics, which cannot be described by the existing MAS models. By means of hybrid system framework and auxiliary variables, a hybrid model of the MAS is constructed to describe the flow dynamics and jumping dynamics. Based on this model, the Lypuanov-based consensus analysis and hybrid ETM design are developed, and the finite-gain L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> stability property is guaranteed. An example of spacecraft formation is provided to show the effectiveness of the proposed approach.

Adaptive Event-Triggered Control for Unknown Second-Order Nonlinear Multiagent Systems

This article investigates adaptive control problems for unknown second-order nonlinear multiagent systems (MASs) via an event-triggered approach. An adaptive event-triggered consensus controller is given to second-order MAS with unknown nonlinear dynamics. We prove that the proposed consensus controller is free from Zeno behavior. Next, an adaptive event-triggered tracking controller is developed for leader-follower MAS with the leader having bounded nonzero control input. Both consensus and tracking controllers are fully distributed, which means that event-triggered controllers only use local cooperative information. Finally, an unknown second-order nonlinear MAS is used to verify the given event-triggered controllers.

Non-fragile H∞ control for body slip angle of electric vehicles with onboard vision systems: The dynamic event-triggering approach

This paper is concerned with the dynamic event-triggered non-fragile H∞ control problem for the body slip angle of electric vehicles subject to parameter variations of vehicle controllers. Dynamics of electric vehicles with an onboard vision system is characterized by a linear model in which the body slip angle, the yaw rate, the lateral offset at the preview point and the vehicle heading angle are chosen as state variables. To reduce the energy consumption in signal transmission, a dynamic event-triggering mechanism is adopted to manage the data transmission between sensors and vehicle controllers. Our aim is to design a non-fragile event-triggered controller such that, for all possible parameter variations in controller gains, all the system states are asymptotically stable and the H∞ performance requirement is met. With the help of the Lyapunov theory, an existence condition of the desired controller is established first and then the desired controller gains are designed in terms of a feasible solution to a matrix inequality. Finally, the effectiveness of the proposed non-fragile H∞ control approach is verified in the electric vehicles.

Asynchronous adaptive quantized feedback sliding mode control for semi-markovian jump systems: An event-triggered approach

This paper is concerned with the problem of event-triggered based asynchronous adaptive quantized sliding mode control (SMC) for Itoˆ stochastic control systems with semi-markovian switching and actuator failures. In this design work, the jump modes between plants and controller are asynchronous, which is represented by a hidden Markov model. The dynamical logarithmic quantizer is introduced in signal quantization both in sensors-to-controller and controller-to-actuators sides, and a new event-triggered detector condition is developed based on the quantized state vector. Combined with SMC and adaptive control techniques, a new event-triggered based asynchronous adaptive quantized SMC law is designed to stabilize the Itoˆ stochastic systems with semi-markovian switching, actuator failures and signal quantization. The proposed control law has ability to guarantee the robust performance of the closed-loop system in the presence of the effects of actuator failures, time delay resulting by event-triggered and signal quantization error. Moreover, the developed event-triggered based asynchronous adaptive quantized feedback SMC scheme can ensure that the sliding surface converges the defined small domain in finite time. The lower bound for inter-execution time is analyzed and presented, and sufficient condition under which the zenor behaviors can be avoided is given. Finally, an example is provided to demonstrate the effectiveness of the proposed design techniques.

Distribution feeder-level multi-temporal coordination of electric vehicle charging flexibilities considering rebound impact and vehicle owner preferences

Charging flexibility management studies have been dominantly structured on daily planning, assuming highly accurate predictions and the availability of large amounts of information. On the other hand, event-triggered approaches using the information of ongoing charging sessions may be more applicable. Moreover, an important gap has been consideration of electric vehicle (EV) owner preferences (e.g. minimum state of charge (SoC) to be reserved) so far. This work investigates multi-temporal coordinated management of EV charging flexibilities. An event-triggered approach that coordinates the ongoing charging sessions using a scalable time window, considering all the time periods affected by the rebound impacts is proposed. Additionally, EV owner preferences in charging (minimum desired increment in SoC per charging sessions) are taken into account by the management logic to ensure user-defined levels of SoC at departure times. A case study with 55 customers in a low-voltage distribution area is explored to compare the effectiveness of the proposed approach and simple charging management based on achieving the biggest reduction in the current hour without considering rebound impacts.

Saving Tokens in Rollout Control with Token Bucket Specification

We consider a communication network over which transmissions must fulfill the so-called token bucket traffic specification, with a rollout (i.e., predictive) controller that both schedules transmissions and computes the corresponding control values. In the token bucket specification, a transmission is allowed if the current level of tokens is above a certain threshold. Recently, it has been shown that having a full bucket at the time of a set point change significantly improves the control performance as compared to when the bucket level is low. In this work, we develop mechanisms that guarantee that the bucket fills up after the controlled plant has converged to a set point. To do this, we consider two different setups. First, we consider that all transmissions over the network must fulfill the token bucket specification and show convergence to the upper sector of the bucket by adding a slight terminal cost on the bucket level. Afterwards, we consider a modified network which additionally features a direct link over which transmissions need not fulfill the token bucket specification. In this setup, we prove convergence of the bucket level exactly to the upper rim. These mechanisms enable a similar level of flexibility as event-triggered control: In converged state, little communication is used while in precarious operating conditions, a burst of transmissions is possible. Other than event-triggered approaches, the proposed methods allow to specify the network traffic beforehand by means of the token bucket. Lastly, we validate the proposed approaches in a numerical example.

Fault Tolerant Control Scheme for a Class of Interconnected Nonlinear Time Delay Systems Using Event-Triggered Approach

In this study, the event-triggered decentralized fault tolerant control (FTC) problem is investigated for a class of interconnected nonlinear time delay systems in strict feedback form with input quantization and actuator faults. The model of interconnected nonlinear time delay systems includes unstructured uncertainties and unmeasurable states. Firstly, the radial basis function neural networks (RBFNNs) are introduced to identify the unstructured uncertainties and time delay functions. An adaptive RBFNNs state observer is constructed to identify the unmeasurable states, which will be used to the design of decentralized fault tolerant controller. By utilizing the adaptive backstepping technique with low pass filter, an event-based decentralized FTC strategy is developed for the considered interconnected nonlinear systems, such that the output signals could track the reference signals, and the stability of the closed loop systems is guaranteed. Finally, the effectiveness of the designed control strategy is illustrated by a practical simulation example.

Resource management using a simulation model of the production process

Two approaches to creating a simulation model of the production process are presented. The purpose of the article is to determine the amount of inventory for the production of products. The process of manufacturing products in the form of a queuing system (QS) is described in AnyLogic by using a discrete event-trigger approach. The system-dynamic approach permits to develop a calculation tool (PI regulator), which was added to the created model. The use of a PI regulator in a simulation model of the production process is most effective at fulfillment a large number of orders. Keywords simulation modeling; the concept of lean manufacturing; resource management; PI regulator

Event-triggered Approach to Increasing Sampling Period of Encrypted Control Systems

Controller encryption is a cryptographic approach to enhancing the security of networked control systems. The method would be effective in reducing risks of eavesdropping attacks. However, encryption may cause high communication traffic and processing delays. This study proposes a redetermination method for a sampling period of a given encrypted control system to increase the sampling period. The proposed method can reduce the bit rate of communication between a plant and controller and improving the strength of ciphertexts. The validity of the proposed method is examined through numerical simulations. The simulation results demonstrate that the sampling period-redetermined encrypted control system achieves asymptotic stability and retains control performance of the original encrypted control system.

Improved Event-Triggering Scheme for Uncertain Systems

This paper develops a new event-triggering approach for a class of nonlinear systems. This approach goes beyond the control of certain systems by developing sporadic feedback control laws to solve unstructured uncertainty problem. It guarantees asymptotic stability of a broad range of uncertain systems under sample and hold implementation while it efficiently reduces the communication samples. Under the proposed scheme, in order to handle the uncertain dynamics, the sampling time might become smaller than that in the approach of the certain systems. Using linear matrix inequalities, the controller gains and the event triggering parameters are obtained simultaneously. In addition to addressing new scheme for uncertain systems, we propose another triggering mechanism for affine nonlinear systems. Simulation results illustrate that the increase of triggered messages due to the nonlinearity and uncertainty is kept small enough that can be neglected when compared with conventional event-triggering policy.

An Event-Triggering Approach to Recursive Filtering for Complex Networks With State Saturations and Random Coupling Strengths.

In this article, the recursive filtering problem is investigated for a class of time-varying complex networks with state saturations and random coupling strengths under an event-triggering transmission mechanism. The coupled strengths among nodes are characterized by a set of random variables obeying the uniform distribution. The event-triggering scheme is employed to mitigate the network data transmission burden. The purpose of the problem addressed is to design a recursive filter such that in the presence of the state saturations, event-triggering communication mechanism, and random coupling strengths, certain locally optimized upper bound is guaranteed on the filtering error covariance. By using the stochastic analysis technique, an upper bound on the filtering error covariance is first derived via the solution to a set of matrix difference equations. Next, the obtained upper bound is minimized by properly parameterizing the filter parameters. Subsequently, the boundedness issue of the filtering error covariance is studied. Finally, two numerical simulation examples are provided to illustrate the effectiveness of the proposed algorithm.

Exponential L1 Filtering of Networked Linear Switched Systems: An Event-Triggered Approach

The issues of event-triggered exponential L1 filtering are studied for a class of networked linear switched systems. An event-triggered mechanism is proposed to enhance resource utilization in transmission, and save the communication cost of systems as well. Then, the filtering error system is reconstructed as a switched delay system with bounded disturbance through the input delay system approach. By resorting to the Lyapunov-Krasovskii functional approach and the average dwell time (ADT) technique, some interesting results are derived to guarantee the exponential stability with a prescribed L1 disturbance rejection level. Further, an event-triggered exponential L1 filter is designed via solving a set of feasible linear matrix inequalities (LMIs). Finally, the efficiency of the proposed results is verified through a numerical example and a PWM-driven boost converter circuit system.

An Event-Triggered Approach to Robust Fault Detection for Nonlinear Uncertain Markovian Jump Systems with Time-Varying Delays

In this paper, the problem of robust fault detection is investigated for nonlinear uncertain Markovian jump systems subject to time-varying delays, Lipschitz nonlinearities and parameter uncertainties under the event-triggered protocol. The event-triggered mechanism is introduced to adjust the transmission frequency of the data sent to the remote module. An event-based fault detection method is presented to guarantee the sensitivity of residual to fault and the attenuation of the effect from the disturbance on the residual. In this way, the considered fault detection problem is solvable by testifying the feasibility of $$H_\infty $$ filtering problem. By constructing the mode-dependent Lyapunov functional, new sufficient criteria are derived in terms of the linear matrix inequality technique, which insures the stochastic stability with prescribed performance for addressed MJSs. In the end, a numerical example is exploited and the validity of newly presented event-based fault detection method is shown.

A Dynamic Event-Triggered Approach to Recursive Filtering for Complex Networks With Switching Topologies Subject to Random Sensor Failures.

This article deals with the recursive filtering issue for a class of nonlinear complex networks (CNs) with switching topologies, random sensor failures and dynamic event-triggered mechanisms. A Markov chain is utilized to characterize the switching behavior of the network topology. The phenomenon of sensor failures occurs in a random way governed by a set of stochastic variables obeying certain probability distributions. In order to save communication cost, a dynamic event-triggered transmission protocol is introduced into the transmission channel from the sensors to the recursive filters. The objective of the addressed problem is to design a set of dynamic event-triggered filters for the underlying CN with a certain guaranteed upper bound (on the filtering error covariance) that is then locally minimized. By employing the induction method, an upper bound is first obtained on the filtering error covariance and subsequently minimized by properly designing the filter parameters. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed filtering scheme.

Event-triggered sliding mode control of nonlinear dynamic systems

In this work, the problem of sliding mode observer design is investigated for a class of repeated scalar nonlinear systems via dynamic event-triggered approach. By constructing an event-triggered observer and a sliding mode surface, the system dynamics is obtained and an event-triggered controller is designed to ensure that the closed-loop system trajectories are restricted to the pre-specified sliding region. Sufficient conditions are provided to guarantee that the system dynamics is asymptotically stable with a desired H∞ performance level. Two illustrative examples are provided to demonstrate the effectiveness and potential of the proposed design method.

Practical Finite-Time Fuzzy Control for Hamiltonian Systems via Adaptive Event-Triggered Approach

This paper is to present our new results on practical finite-time fuzzy control scheme for a class of Hamiltonian systems by an adaptive event-triggered approach. An unknown function of the system is approximated by an adaptive fuzzy system. According to a semi-global practical finite-time stability criterion, a novel adaptive fuzzy finite-time controller is presented. In the interest of saving resources, an event-triggered approach is developed where the controller is updated under the respective triggering conditions. Based on the special structure of Hamiltonian systems and Lyapunov theory, a sufficient condition is obtained so that the states of original systems converge to a small neighborhood containing the origin in a finite time. Meanwhile, with the proposed controller, there exists a positive lower bound for the interexecution time, and the Zeno phenomenon is avoided. The design processes of the proposed controller, adaptive law and event-triggered conditions are also proved by a circuit system simulation example.

On the Secondary Control Architectures of AC Microgrids: An Overview

Communication infrastructure (CI) in microgrids (MGs) allows for the application of different control architectures for the secondary control (SC) layer. The use of new SC architectures involving CI is motivated by the need to increase MG resilience and handle the intermittent nature of distributed generation units. The structure of SC is classified into three main categories, including centralized SC (CSC) with a CI, distributed SC (DISC) generally with a low-data-rate CI, and decentralized SC (DESC) with communication-free infrastructure. To meet the MGs' operational constraints and optimize performance, control and communication must be utilized simultaneously in different control layers. In this survey, we review and classify all types of SC policies from CI-based methods to communication-free policies, including CSC, averaging-based DISC, consensus-based DISC methods, containment pinning consensus, event-triggered DISC, washout-filter-based DESC, and state-estimation-based DESC. Each structure is scrutinized from the viewpoint of the relevant literature. Challenges such as clock drifts, cyber-security threats, and the advantage of event-triggered approaches are presented. Fully decentralized approaches based on state-estimation and observation methods are also addressed. Although these approaches eliminate the need of any CI for the voltage and frequency restoration, during black start process or other functionalities related to the tertiary layer, a CI is required. Power hardware-in-the-loop experimental tests are carried out to compare the merits and applicability of different SC structures.