Event-triggered Control Design Research Articles

Observer-Based Event-Triggered Containment Control for MASs Under DoS Attacks.

This article studies the observer-based event-triggered containment control problem for linear multiagent systems (MASs) under denial-of-service (DoS) attacks. In order to deal with situations where MASs states are unmeasurable, an improved separation method-based observer design method with less conservativeness is proposed to estimate MASs states. To save communication resources and achieve the containment control objective, a novel observer-based event-triggered containment controller design method based on observer states is proposed for MASs under the influence of DoS attacks, which can make the MASs resilient to DoS attacks. In addition, the Zeno behavior can be eliminated effectively by introducing a positive constant into the designed event-triggered mechanism. Finally, a practical example is presented to illustrate the effectiveness of the designed observer and the event-triggered containment controller.

An Improved Design of Event-Triggered Feedback Controllers for Linear Systems Based on Fast and Slow Dynamics

In this article, an event-triggered technique is proposed to implement state feedback controllers for continuous-time linear systems. Toward this end, the closed-loop dynamic is decomposed into the fast and slow subsystems. Then, two individualized event-triggered mechanisms (ETMs) are designed to compute two sequences of updates. The first ETM determines when the fast subsystem should be sampled and its measured data should be sent to the controller. The second ETM decides the execution times for sampling all the system states, including both the fast and slow states. The proposed event-triggered technique leads to sampling policies in which the data of the slow states are sent to the controller with long interevent intervals whereas the fast dynamics are simultaneously allowed to be sampled with relatively shorter interevent intervals. In comparison with conventional methods with one ETM, the proposed event-triggered technique, equipped with an extra degree of freedom, leads to better results both in achieving smoother closed-loop responses and reducing the number of the transmitted packages from the system to the controller. Theoretical aspects of the proposed method including the boundedness of the system and its Zeno free property are investigated. Two simulation and experimental case studies are provided to show the effectiveness of the proposed event-triggered controller.

Dynamic Event-Triggered Design With Fixed-Time Performance and Input Dead-Zone

This brief develops a novel fixed-time dynamic event-triggered control design for strict-feedback nonlinear systems with an input dead-zone. Compared with static event-triggered control, a dynamic event-triggering condition is designed to reduce the computation and communication burden. A novel compensation filter is designed to compensate for the input dead-zone and can be utilized to eliminate the influences of input dead-zone on control design. Furthermore, novel command filters (CFs) are introduced to deal with the explosion of complexity. Both the proposed novel compensation filter and CFs can achieve fixed-time performance. The presented method is validated using a jerk circuit system.

Dynamic event‐triggered control for a class of p‐normal nonlinear time‐delay systems via output feedback

ABSTRACTIn this article, the event‐triggered (ET) output feedback control problem is discussed for a class of ‐normal nonlinear time‐delay systems. Different from the related existing literature, the linear growth condition is relaxed to the homogeneous one and the growth rate is unknown. In the case of unknown time‐varying delays and control coefficients, nonsmooth control law and some extra redundant terms will be encountered in the design of ET controller, which would bring substantial challenges to the achievement of global convergence. To cope with unknown growth rate and time‐varying delays, two dynamic gains and an appropriate Lyapunov–Krasovskii functional (LKF) are introduced. Then, a new dynamic ET mechanism is given, in which the triggering threshold can be tuned dynamically. It is proved that all the signals of the closed‐loop system (CLS) are bounded. Corresponding examples are given to indicate the validity of the developed theoretical results.

On the Design of Event-Triggered Consensus-Based Secondary Control of DC Microgrids

Voltage regulation and proper load-sharing are two main control objectives of DC microgrids which the consensus-based secondary control can be regarded as a feasible approach to achieve them. Using this approach, in addition to the stable voltage regulation, the load is shared according to the nominal potential of the distributed generation units. Nevertheless, the conventional consensus-based secondary control uses the time-triggered communication paradigm that leads to a high communication burden due to transmitting and receiving unnecessary data. In this paper, to prevent excessive data-exchanging, the mentioned approach is upgraded with a novel event-triggered scheme. The system stability analysis under the suggested event-triggered secondary controller is assessed using the Lyapunov theorem. Furthermore, the Zeno-freeness feature of the proposed solution is mathematically proved after assessing uniformly ultimately bounded stability and extracting the current per-unit and voltage derivatives dynamic as the consensus algorithm’s external inputs. The proposed approach is applied to a DC microgrid, and its performance is validated under different scenarios using Simulink/MATLAB environment. Moreover, the experimental tests prove the merits of the suggested method.

Adaptive Fuzzy Event-Triggered Tracking Control for Nonstrict Nonlinear Systems

This article addresses adaptive fuzzy event-triggered controller design for nonstrict nonlinear systems. First, for estimating the unmeasurable states, the high-gain fuzzy state observer is designed. By using backstepping technique, the adaptive fuzzy controller is designed. A new switching threshold event-triggered mechanism is given to decide when the controller needs to be updated and the Zeno behavior is avoided. Stability analysis shows that the tracking error can be arbitrarily small and all variables of the closed-loop system remain bounded. At last, the effectiveness of our control strategy is illustrated through simulation.

Event-triggered controller design for positive T-S fuzzy systems with random time-delay

This paper is concerned with the design of event-triggered controller for positive Takagi-Sugeno (T-S) fuzzy systems with a random time-delay. The random time-delay is described as a Markov process. A controller switched at different event-triggered instant is proposed. By constructing a new event-triggered instant-dependent linear co-positive Lyapunov function, the design criteria of event-triggered controller is derived to ensure the positivity and stability of the closed-loop system. These criteria can be solved by linear programming (LP) technique. A positive lower bound on the inter-execution time is ensured, which means that there is Zeno-free phenomenon. Finally, the simulation has demonstrated the effectiveness and merit of the proposed results.

Integrated Design of Event-triggered Control and Mobile Non-collocated SANs for a Diffusion Process

Integrated Design of Event-triggered Control and Mobile Non-collocated SANs for a Diffusion Process

An Event-Triggered Observer and Its Applications in Cooperative Control of Multiagent Systems

This article proposes an event-triggered control design for cooperative control of heterogeneous multiagent systems. The design is serial in nature and consists of the design of a distributed event-triggered observer for each follower agent that estimates the desired information of the leader system in the presence of parametric uncertainty and, based on this observer, the design of a distributed event-triggered controller. A salient feature of our observer design is that it obeys the separation principle in the sense that the event-triggered control can be designed after the observer has been designed. As a result, the observer is applicable to different follower agent dynamics and the event-triggered time sequence for the controller is asynchronous of that of the observer. We implement this design scheme on linear heterogeneous multiagent systems and uncertain Euler–Lagrange multiagent systems, and achieve results that significantly extend the existing ones.

Asynchronous Control for Switched T–S Fuzzy Systems Subject to Data Injection Attacks via Adaptive Event-Triggering Schemes

This article addresses the asynchronous event-triggered control problem for switched Takagi–Sugeno (T–S) fuzzy systems under data injection attacks. In reducing communication data update frequency, event-triggered control is an effective control method. The periodic sampling-based adaptive event-triggering schemes with switching structure are first proposed, which can dynamically adjust triggered conditions based on system performance. It is assumed that only the event-triggered and quantized data of the system state and the event-triggered switching signal are available for controllers. However, since the switching signal is sampled and triggered, asynchronous switching may occur between subsystems and subcontrollers. Furthermore, the data injection attacks are considered in the communication network of the system. A time-delay closed-loop switched T–S fuzzy system model is obtained by using a model transformation technique. The resulting criterion provides sufficient conditions to ensure that the closed-loop system subject to data injection attacks is exponential stability with 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> performance. Moreover, a set of conditions for the co-design of controllers and adaptive event-triggering schemes is presented. Finally, simulations are given to verify the effectiveness of the asynchronous event-triggered control design.

Periodic event-triggered adaptive tracking control design for nonlinear discrete-time systems via reinforcement learning

In this paper, an event-triggered control scheme with periodic characteristic is developed for nonlinear discrete-time systems under an actor–critic architecture of reinforcement learning (RL). The periodic event-triggered mechanism (ETM) is constructed to decide whether the sampling data are delivered to controllers or not. Meanwhile, the controller is updated only when the event-triggered condition deviates from a prescribed threshold. Compared with traditional continuous ETMs, the proposed periodic ETM can guarantee a minimal lower bound of the inter-event intervals and avoid sampling calculation point-to-point, which means that the partial communication resources can be efficiently economized. The critic and actor neural networks (NNs), consisting of radial basis function neural networks (RBFNNs), aim to approximate the unknown long-term performance index function and the ideal event-triggered controller, respectively. A rigorous stability analysis based on the Lyapunov difference method is provided to substantiate that the closed-loop system can be stabilized. All error signals of the closed-loop system are uniformly ultimately bounded (UUB) under the guidance of the proposed control scheme. Finally, two simulation examples are given to validate the effectiveness of the control design.

Subpredictor approach for event-triggered control of discrete-time systems with input delays

We propose a new output event-triggered control design for linear discrete-time systems with constant arbitrarily long input delays, using delay compensating subpredictors. We prove input-to-state stability of the closed loop system, using framers and the theory of positive systems. A novel feature of our approach is our use of matrices of absolute values, instead of Euclidean norms, in our discrete-time event triggers for our delay compensating control design. We illustrate our approach using a model of the BlueROV2 marine vehicle, where our new event triggers lead to a smaller number of control recomputation times as compared with standard event triggers that were based on Euclidean norms, without sacrificing on settling times or on other performance metrics.

Event-Triggered Antidisturbance Control Design for Aeroengine Systems via Switched Models

In this paper, an event-triggered antidisturbance (ETAD) control scheme is presented for a category of aeroengine control systems (AECSs) involved in multiple disturbances. First, an AECS in this category is described by a switched model at a series of steady-state points. Then, a dynamic event-triggered mechanism is introduced by constructing the ET condition based on the control input directly, saving the signal transmission resource from the controller to the AECS. Next, a switching law with sampling is developed, economizing the signal transmission resource from the switching law to the AECS. Furthermore, based on the ET mechanism and switching law, an antidisturbance controller is designed to compensate for or suppress the influence of the multiple disturbances on the AECS. Also, under the ETAD control approach, relative theoretical conditions are established to save the signal transmission resource and to suppress or compensate multiple disturbances. Finally, using a hardware-in-loop platform with a switched aeroengine model inserted, a simulation is implemented to validate how the established ETAD control strategy is effectively applied to the AECS.

A Learning Approach for Joint Design of Event-Triggered Control and Power-Efficient Resource Allocation

In emerging Industrial Cyber-Physical Systems (ICPSs), the joint design of communication and control sub-systems is essential, as these sub-systems are interconnected. In this paper, we study the joint design problem of an event-triggered control and an energy-efficient resource allocation in a fifth generation (5G) wireless network. We formally state the problem as a multi-objective optimization one, aiming to minimize the number of updates on the actuators' input and the power consumption in the downlink transmission. To address the problem, we propose a model-free hierarchical reinforcement learning approach \textcolor{blue}{with uniformly ultimate boundedness stability guarantee} that learns four policies simultaneously. These policies contain an update time policy on the actuators' input, a control policy, and energy-efficient sub-carrier and power allocation policies. Our simulation results show that the proposed approach can properly control a simulated ICPS and significantly decrease the number of updates on the actuators' input as well as the downlink power consumption.

Event-triggered controller design for LTI systems: A distributed interval observer-based approach

This paper investigates the distributed event-triggered control design problem for networked linear time-invariant (LTI) systems with partially measurable states, in the presence of bounded external disturbances. A distributed interval observer-based event-triggered control scheme has been proposed, the main features of this scheme lie in a) designing a novel distributed interval observer to deal with the unknown states and bound disturbances problem; b) proposing a distributed feedback control method using interval estimation information, the partially measurable limitation has been solved; c) introducing a decreased time-varying function with dead-zone modification to avoid the Zeno behavior. Moreover, sufficient conditions for the stability of closed-loop systems are given in the Lyapunov sense by using matrix inequalities and transmission strategy. Finally, the uniformly ultimately bounded stability and Zeno behavior avoidance of the proposed approach have been numerically demonstrated.

Fuzzy event-triggered control for nonlinear networked control systems

This paper is focus on an event-triggered control design problem for nonlinear networked control systems with missing data and transmission delay in the interval type-2 (IT2) fuzzy form. An event-triggered controller is presented under a sampled-state-error mechanism. By dividing the event-triggered interval into some subsets, stability analysis is carried out based on Lyapunov-Krasovskii functional (LKF), and the stability of the closed-loop system is ensured. The proposed design is applied to the continuous stirred tank reactor system (CSTR) and the manipulator system. The control strategy is effective, and the merit of the event-triggered mechanism is indicated.

Toward Embedded System Resources Relaxation Based on the Event-Triggered Feedback Control Approach

The paper describes an event-triggered nonlinear feedback controller design. Event triggering is a real-time controller implementation technique which reduces embedded system utilization and relaxes task scheduling of the real-time system. In contrast to classic time implementation techniques, the event-triggered execution is validated regarding the introduced triggering policy. The triggering rule is a boundary, where the last task value is preserved until the rule is violated. In the given paper, two different event-triggered strategies are designed for the class of dynamic systems with integral behavior. Both methods are based on sliding mode controller design, where the triggering rule of the first design involves only a partial state vector, which is a direct consequence of the triggering rule derivation throughout the Lyapunov stability analysis. In the second approach, the sliding mode controller is designed upon prior stabilized systems with the additional term, which enables derivation of the triggering rule based on the whole state vector. The second approach offers better closed-loop performance and higher relaxation of the system utilization. The selection of triggering boundary is related closely to the derived minimal inter-event time, which impacts the computational burden of the real-time system and closed-loop performance directly. The derived controllers are compared with the classic sample and hold implementation techniques. The real-time results are presented, and system performances are confirmed regarding embedded system task relaxation, lowering the computational intensity and preserving closed-loop dynamics.

Event-triggered impulsive control design for synchronization of inertial neural networks with time delays

This paper investigates the synchronization problem of inertial neural networks (INNs) with time delays by virtue of event-triggered (E-T) impulsive control, in which a Lyapunov function based E-T mechanism is used to determine impulsive instants. The synchronization analysis of INNs through E-T impulsive control technique unlike time-triggered impulsive control, which would be activated when certain well-designed conditions exist, E-T impulsive control is only allowed when certain well-defined events occur. Besides that, control input is only required at triggered instants and also no control input is required for two triggered instants in a sequence. Considering the E-T mechanism, the synchronization analysis of the INNs is discussed by reduced and non-reduced order approaches and constructing the suitable Lyapunov functionals. Finally, two simulation results are provided to illustrate the efficacy of the theoretical results.

Dynamic event-triggered control design for a class of [formula omitted]-normal nonlinear time-delay systems with actuator failures

This paper investigates the adaptive tracking control problem for a class of p-normal nonlinear time-delay systems with actuator failures via a dynamic event-triggered strategy. To deal with the time-varying delay, a modified Lyapunov-Krasovskii functional (LKF) with the system powers is constructed. By using radial basis function neural networks and hyperbolic tangent function, the residual terms caused by the derivative of LKF can be handled. Then, to achieve better communication efficiency, a dynamic event-triggered strategy is proposed, in which the threshold parameter is dynamically adjusted with the change of the virtual control signal. With the help of the proposed adaptive controller, all states of the closed-loop system are bounded and a favorable tracking performance is ensured. Finally, two examples are given to demonstrate the effectiveness of the proposed method.

A Novel Event-Triggered Control of DC Microgrids Against Probabilistic Actuator Fault

This article investigates a problem of event-triggered controller design for DC microgrid, in which multiple nonlinear Constant power loads (CPLs) and probabilistic actuator fault are considered. A novel pre-averaged event-triggered mechanism (PAETM) is put forward, under which the average value of each time interval is used to determine the triggering instead of using the sample data that represents the system characteristic partially. Benefit from this mechanism, triggering events are reduced and the network burden is mitigated while the system performance is ensured, which contributes to a higher efficiency for DC microgrid. Considering various disturbances in DC microgrid, a unified PAETM controller design for DC microgrid with probabilistic distribution actuator fault and disturbance is proposed. Finally, a simulation example is shown to illustrate the validity of the proposed control strategy.