Dynamic Event-triggered Mechanism Research Articles

Distributed state-of-charge estimation for lithium-ion batteries with random sensor failure under dynamic event-triggering protocol

The state of charge (SOC) performs as an indicator of the remaining capacity of the Lithium-ion batteries (LBs). An accurate SOC estimation of LB is of great significance for its operation optimization and life extension of the battery. In this article, the issue of distributed SOC estimation is addressed for LBs. To design the distributed filter for SOC estimation, the equivalent circuit model comprised of the resistor–capacitor networks, Warburg element, ohmic resistance, battery current and voltage is established. In order to reflect the properties of the random sensor failure (RSF) well, a set of Bernoulli-distributed sequences with known probabilities is introduced. The communication resources over the wireless networks are usually limited, for the purpose of saving communication resources, the dynamic event-triggering mechanism (DETM) is adopted to regulate transmission of the signals. The main objective of this article is to design a distributed SOC estimation approach for LBs subject to RSF under DETM over the sensor networks. The upper bound of the estimation error covariance is first ensured and then such upper bound is minimized by parameterizing the estimator gain. In addition, by virtue of the matrix simplification technique, the issue of sensor network topology’s sparseness is effectively tackled. At last, experimental examples are employed to validate the feasibility of the developed distributed SOC estimation algorithm.

Dynamic event-triggered control for discrete-time nonlinear Markov jump systems using policy iteration-based adaptive dynamic programming

This paper investigates a dynamic event-triggered optimal control problem of discrete-time (DT) nonlinear Markov jump systems (MJSs) via exploring policy iteration (PI) adaptive dynamic programming (ADP) algorithms. The performance index function (PIF) defined in each subsystem is updated by utilizing an online PI algorithm, and the corresponding control policy is derived via solving the optimal PIF. Then, we adopt neural network (NN) techniques, including an actor network and a critic network, to estimate the iterative PIF and control policy. Moreover, the designed dynamic event-triggered mechanism (DETM) is employed to avoid wasting additional resources when the estimated iterative control policy is updated. Finally, based on the Lyapunov difference method, it is proved that the system stability and the convergence of all signals can be guaranteed under the developed control scheme. A simulation example for DT nonlinear MJSs with two system modes is presented to demonstrate the feasibility of the control design scheme.

Anti-disturbance attitude quantized control of flexible spacecraft via a triggering and quantization joint dynamic event-triggered mechanism

This article investigates the problem of dynamic event-triggered anti-disturbance attitude quantized control based on the Takagi-Sugeno fuzzy method for flexible spacecraft, where multiple disturbances and parameter uncertainties are simultaneously considered. First, by employing the Takagi-Sugeno fuzzy model to represent the nonlinear disturbances with additional disturbance, a disturbance observer based on the Takagi-Sugeno fuzzy model is constructed under the unmeasurable premise variables to estimate the unknown nonlinear disturbances. Furthermore, a flexible vibration observer is formatted. Subsequently, a dynamic event-triggered mechanism with the quantization parameter is introduced, which can obtain a trade-off between quantization density and event-triggered frequency on the condition that the system stability is ensured. And an event-triggered anti-disturbance quantized controller is constructed, which can make up for Takagi-Sugeno fuzzy modeling disturbances and reject parameter uncertainties and other bounded disturbances. To guarantee the bound of the closed-loop signals, some sufficient conditions are obtained. At last, the efficiency of the suggested control strategy is illustrated via the simulation results.

Dynamic event-triggered adaptive fuzzy control for stochastic nontriangular nonlinear systems with unknown backlash-like hysteresis

A finite-time adaptive control is discussed in this paper for stochastic nontriangular nonlinear systems with unknown backlash-like hysteresis. The performance function is introduced to ensure that the tracking error of the system converges to the specified region in a finite time. Secondly, a controller is proposed using the fuzzy logic systems to approximate the unknown functions and backstepping technique. In addition, adding the dynamic event-triggered mechanism is able to reduce the network resources more effectively. At last, a few simulation examples are presented to demonstrate effective performance.

Dynamic event-triggered adaptive control for zero-sum games of nonlinear stochastic systems

This paper considers solving the zero-sum games (ZSGs) of nonlinear stochastic systems under the architecture of dynamic event-triggered mechanism (DETM). The adaptive dynamic programming (ADP) approach with great approximate computing power is proposed to seek the saddle-point equilibrium solution of ZSGs. First, the Hamilton–Jacobi–Isaacs equation of stochastic version is constructed which is the key to solving the two-player ZSGs. Then, the ADP method is employed to search the approximated solution under the dynamic triggering mechanism. On the foundation of static event-triggered mechanism (SETM), the DETM is derived through introducing an internal dynamic invariable to further lower the update frequency for the strategies. Additionally, the stability of the closed system is demonstrated in detail via the Lyapunov theory. Finally, two representative examples are provided to present the availability and reliability of this approach from different perspectives.

Fixed-Time Average Consensus of a Dynamic Event-Triggered Mechanism in a System of Multiple Underactuated Autonomous Underwater Vehicles Based on a Body Frame Spherical Coordinate System

This paper is concerned with the consensus of a system involving multiple underactuated autonomous underwater vehicles (AUVs). Combined with a dynamic event-triggered mechanism and a fixed-time stability theorem, the backstepping average consensus controllers are designed. Firstly, the new consensus control objective on the system for multiple underactuated AUVs in a body frame (BF) spherical coordinate system is proposed, and the tracking error kinematic equations are established based on the kinematic characteristics of the underactuated AUV. The fixed-time consensus controller is designed by the backstepping method, and the average consensus theorem is proposed to improve the Lyapunov function. Furthermore, the dynamic event-triggered mechanism is adopted to reduce the communication requirements and energy consumption. This is the first solution to the problem of a consensus controller design for a system of multiple underactuated AUVs. Finally, numerical simulation results demonstrate that the proposed method has superior effectiveness over alternatives.

Dynamic event-triggered formation control for UAVs under communication delay and outside disturbances

This work presents a dynamic event-triggered sliding mode controller to solve the problem on cooperative formation flight for unmanned aerial vehicles (UAVs) under outside disturbances and communication delay. Initially, a second-order kinematic model for each UAV is established, and the leader-follower framework is adopted to realize the desired formation flight. Second, an effective design of disturbance observer is proposed based on that the disturbance in the UAV is generated by an external nonlinear system. Third, a new dynamic event-triggered mechanism (DETM) is presented and the triggering threshold is adjusted by an exogenous system, which can help reduce data transmissions and maintain control performance more efficiently. Then, a distributed dynamic event-triggered sliding mode control strategy is proposed for the UAV system, and two sufficient conditions on exponential stability of the overall closed-loop system are derived. Furthermore, the controller gain, observer gain, and triggering parameter can be obtained by solving the derived linear matrix inequalities (LMIs). Finally, a simulated example is exploited to illustrate the obtained results.

Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.

Distributed Formation-Containment Control for Discrete-Time Multiagent Systems Under Dynamic Event-Triggered Transmission Scheme

In this article, the distributed formation-containment (FC) control issue is investigated for a class of discrete-time multiagent systems (DT-MASs) under the event-triggered communication mechanism. In order to save the communication cost and improve the utilization of communication resources, a novel dynamic event-triggered (DET) mechanism is developed by adding an auxiliary variable for each agent system, which is able to dynamically adjust the triggering threshold. A distributed FC control scheme under the DET mechanism is proposed for all the leaders and followers based on the available relative outputs. The purpose of the addressed problem is to design the FC controller such that all the leaders achieve a formation shape and all the followers converge into such a convex hull. To this end, the considered DT-MASs are first decoupled into a diagonal form by resorting to the property of the Laplacian matrix as well as the inequality technique. Then, two sufficient conditions are established to ensure the desired FC performance. Furthermore, the corresponding FC controller parameters are obtained in terms of the solutions to two matrix inequalities which only depend on the maximum and minimum nonzero eigenvalues of the Laplacian matrix. Finally, an illustrative example is provided to verify the validity of the developed control scheme.

Hybrid Dynamic Event-Triggered Load Frequency Control for Power Systems With Unreliable Transmission Networks.

In this article, we consider the load frequency control problem for a class of power systems based on the dynamic event-triggered control (ETC) approach. The transmission networks are unreliable in the sense that malicious denial-of-service (DoS) attacks may arise in the power system. First, a model-based feedback controller is designed, which utilizes estimated states, and thus can compensate the error between plant states and the feedback data. Then, a dynamic event-triggered mechanism (DETM) is proposed by introducing an internal dynamic variable and a timer variable with jump dynamics. The proposed (DETM) can exclude Zeno behavior by regularizing a prescribed strictly positive triggering interval. Incorporated in the ETC scheme, a novel hybrid model is established to describe the flow and jump dynamics of the power system in the presence of DoS attacks. Based on the hybrid dynamic ETC scheme, the power system stability can be preserved if the attacks frequency and duration sustain within an explicit range. In addition, the explicit range is further maximized based on the measurement trigger-resetting property. Finally, a numerical example is presented to show the effectiveness of our results.

Dynamic Event-Triggered Adaptive NN Control for Switched Uncertain Nonlinear Systems.

This article is concerned with the problem of dynamic event-triggered adaptive neural network (NN) control for a class of switched strict-feedback uncertainty nonlinear systems. A novel switched command filter-based dynamic event-triggered adaptive NN control approach is set up by exploiting the backstepping and command filter and the common Lyapunov function method. Since adaptive controllers of subsystems are event triggered, then if the switching happens between any two consecutive triggering instants, asynchronous switching will arise between candidate controllers of subsystems and subsystems. Unlike the existing literature, where maximum asynchronous time is restricted, without any strict limitations on maximum asynchronous time being needed in this article, the asynchronous switching problem is directly handled by proposing a novel switching dynamic event-triggered mechanism (DETM) and event-triggered adaptive controllers of subsystems. Moreover, a piecewise constant variable is introduced into the switching DETM, which overcomes the difficulty of switched measurement error being discontinuous. Also, a strictly positive lower bound of interevent times is obtained. Finally, a continuous stirred tank reactor system and a numerical example are presented to demonstrate the effectiveness of the developed approach.

Dynamic Event-Triggered Consensus Control for Leader-Following Multiagent Systems With Communication Delay

This brief considers the dynamic event-triggered consensus control design of leader-following multiagent systems (MASs) under communication delay. Static event-triggered mechanism is often used, but its energy saving is limited. The dynamic event-triggered mechanism based on sampled data can obtain fewer trigger times than static event-triggered mechanism by adding a dynamic variable, which means that energy is saved to a greater extent and Zeno behaviors can be excluded obviously. Different from the existing works, this brief considers time-varying communication delay between agents. A periodic switching controller is used to deal with delay. Besides, the Lyapunov-Krasovskii function is applied to prove the stability of the closed-loop system and linear matrix inequality plays an important role in this process. Finally, simulation results illustrate the availability of the proposed controller.

Finite-time H∞ control for switched fuzzy systems: A dynamic adaptive event-triggered control approach

This paper investigates the finite-time H∞ control problem for switched fuzzy systems using the edge-dependent average dwell time switching. A dynamic event-triggered mechanism is adopted to alleviate communication pressure. An adaptive law is set up to adjust the threshold on-line, which deeply affects the triggering times. It is rigorously proved that the Zeno behavior is excluded. A set of dynamic event-triggered controllers and edge-dependent average dwell time switching signals are co-designed to achieve desired performance. Finally, a chemical reaction example is given to validate the effectiveness of the proposed method.

Consensus control for multi-rate multi-agent systems with fading measurements: the dynamic event-triggered case

This paper studies the distributed -consensus control problem for a class of multi-rate multi-agent systems with fading measurements. A multi-rate sampling strategy is adopted to be more in line with actual need and the channels between each agent and its sensor always fade non-identically. The multi-rate system is transformed into a single-rate system via the lifting technique. For the purpose of reducing the transmission burden, a dynamic event-triggered mechanism is utilized to determine whether the agent's information is allowed to transmit to its neighbours. This paper aims to design an observer-based event-triggered controller for each agent to achieve the -consensus control performance constraint. With the help of the Lyapuonv stability theory, sufficient conditions are obtained that can ensure the desired control performance for the resulting closed-loop systems, and then the desired gain matrices are calculated by solving the linear matrix inequality. Finally, a numerical simulation example is given to demonstrate the effectiveness of the distributed event-triggered consensus control scheme.

Generalized Nash equilibrium seeking for networked noncooperative games with a dynamic event-triggered mechanism

The generalized Nash equilibrium (GNE) seeking problem of networked noncooperative games is addressed in this paper, where the decision set of each agent is coupled with others via shared constraints. To improve the communication efficiency among agents, a semi-decentralized dynamic event-triggered GNE seeking algorithm is proposed under the full-decision information scenario. Further, considering the partial-decision scenario, where each agent only has the direct interaction with its neighbors via a network, a distributed dynamic event-triggered GNE seeking algorithm is proposed on the basis of a consensus protocol and an operator splitting method. Some sufficient conditions are derived to guarantee the convergence to a variational GNE. Finally, examples on Nash-Cournot games and task allocation games are demonstrated to verify the potential and validity of theoretical results.

Dynamic event-triggered distributed observer for linear systems

This paper investigates a dynamic event-triggered distributed observer for linear systems including two groups of local observers: one can access the local outputs and another cannot. By the detectability decomposition, the proposed observer contains a detectable sub-state (DSS) observer and a distributed undetectable sub-state (USS) observer. The dynamic event-triggered mechanism (DETM) for the outputs only requires a copy of the DSS observer with low dimension. Besides, only the USS estimate is transmitted to the neighbors which can reduce the communication burden. Positive minimum inter-event times are prescribed previously in the DETMs, and piece-wise dynamics for internal dynamic variables are employed. By modeling the error systems as hybrid systems, the exponential stability of the proposed observer is assured with the utilization of time-triggering method and event-triggering method.

Decentralized adaptive neural safe tracking control for nonlinear systems with conflicted output constraints

The issue of decentralized adaptive safe tracking control for interconnected large-scale nonlinear systems (ILSNSs) with conflicted output constraints is discussed in this paper. By “conflicted output constraints”, we mean that the output constraint functions conflict with reference signal, i.e., the reference signal is not completely constrained within the constraint range. In existing methods, it is always assumed that the reference signal is constrained within the constraint region. In practice, the constraints may be detected during system operation and conflict with the reference signal given in advance. In this particular case, the existing methods based on barrier Lyapunov function (BLF) or nonlinear transformation function (NTF) are invalid. From a new point of view, this article designs a new safety reference signal (SRS) which is completely restricted within the constraint range by using the boundary protection approach. Meanwhile, a prescribed performance function which can arbitrarily define the convergence time and tracking accuracy is introduced so that the system output can better track the SRS. Then, combining backstepping technique and radial basis function neural network (RBFNN), a new controller is constructed, under which a desired tracking trajectory can be obtained under the premise of ensuring safety performance. Furthermore, by adding a dynamic event triggering mechanism (DETM) between the actuator and the plant, the communication burden is effectively reduced. Simulation results verify the scheme developed.

Dynamic event-triggered [formula omitted] control for markov jump systems with input saturation

This paper is mainly to explore H∞ state feedback control problem for Markov jump systems (MJSs) with input saturation. To avoid the waste of network resources, a dynamic event-triggered mechanism (DETM) is proposed from system plant to controller, which produces a larger interval between two consecutive events compared with the traditional static one. On the basis of this model, sufficient criteria for stochastic stability of the controlled MJSs are derived by linear matrix inequalities (LMIs) and the controllers are designed. Then the maximum estimate of the domain of attraction (DOA) is obtained by the optimization procedure. Finally, examples show that the proposed DETM has better properties of saving resources than static event-triggered mechanism (ETM) while maintaining the same performance.

Dynamic event-triggered adaptive finite-time consensus control for multi-agent systems with time-varying actuator faults.

In this study, the adaptive finite-time leader-following consensus control for multi-agent systems (MASs) subjected to unknown time-varying actuator faults is reported based on dynamic event-triggering mechanism (DETM). Neural networks (NNs) are used to approximate unknown nonlinear functions. Command filter and compensating signal mechanism are introduced to alleviate the computational burden. Unlike the existing methods, by combining adaptive backstepping method with DETM, a novel finite time control strategy is presented, which can compensate the actuator efficiency successfully, reduce the update frequency of the controller and save resources. At the same time, under the proposed strategy, it is guaranteed that all followers can track the trajectory of the leader in the sense that consensus errors converge to a neighborhood of the origin in finite time, and all signals in the closed-loop system are bounded. Finally, the availability of the designed strategy is validated by two simulation results.

Secure Event-Triggered Vehicle Platooning Control with Proportional Integral Observers under Denial of Service Attacks

This paper addresses the problem of secure event-triggered platooning control for multiple automated vehicles where the vehicle-to-vehicle communication network suffers from limited resource constraint and denial-of-service (DoS) attacks. A novel distributed proportional-integral observer (PIO) with a forgetting integral term is first proposed for each platoon vehicle to estimate its full state. In light of the PIOs, a distributed dynamic event-triggered platoon controller is then constructed under a bandwidth-sensitive dynamic event-triggered mechanism (DETM). Furthermore, a switching system model is presented to overcome the challenge of complex time series coming from DETM and DoS attacks. A sufficient co-design condition is derived to receive the desired controller gain. Finally, an illustrative example is provided to validate the derived main results.