Dynamic Event-triggered Control and Estimation: A Survey

In this paper, an adaptive dynamic event-triggered output-feedback control scheme is proposed for a class of uncertain nonlinear systems. Specifically, a parameter estimator and a Nussbaum function are incorporated into the dynamic event-triggered control scheme to compensate for serious uncertainties, including the completely unknown parameter allowed in system nonlinearities and the unknown control coefficients (both signs and magnitudes are unknown). Importantly, an additional internal dynamic variable is introduced into the event-triggering mechanism, enabling the control scheme to save network resources more efficiently compared with the static ones in the related works. In addition, by skillfully designing the dynamics of this variable, the influence of the execution error can be fully counteracted. It is shown that, with the proposed control scheme, the system states can asymptotically converge to zero, instead of to a residual set, while excluding the Zeno phenomenon. To validate the effectiveness and superiority of the proposed scheme, two simulation examples are provided.

Tracking control of surface vessel systems with disturbances and deferred full state constraints.

This paper investigates the cooperative output regulation problem for heterogeneous linear multiagent systems under fixed communication graphs via event-triggered control. A fully distributed event-triggered dynamic output feedback control law is proposed based on the feedforward design approach. At the same time, a fully distributed dynamic event-triggering mechanism is designed so that each agent can determine when to broadcast its information to its neighbors. Compared with existing related results, both the control law and the event-triggering mechanism in this paper are independent of any global information. It is shown that with the proposed dynamic event-triggered control strategy, the cooperative output regulation problem can be solved in a fully distributed manner by intermittent communication. Moreover, Zeno behavior can be strictly ruled out for each agent. Finally, the effectiveness of the proposed dynamic event-triggered control strategy is validated by a numerical example.

Dynamic event-triggered composite anti-disturbance fault-tolerant tracking control for ships with disturbances and actuator faults

In this paper, an additional internal dynamic variable is introduced into the continuous event-triggered mechanism (ETM) and the discrete ETM, respectively, reducing the number of triggers. The closed-loop system with time-varying communication delays and dynamic event-triggered control (ETC) is modeled as a time-delay system model. The stability and stabilization criteria are derived based on Lyapunov-Krasovskii (L-K) functional method, and a tighter delay-dependent condition in terms of linear matrix inequalities (LMIs) is obtained. By solving these LMIs, we can gain a joint-design method so that the state-feedback controller gain and the event-triggered strategy are obtained at the same time. The results can provide trade-offs between required communication resources and desired control performance. The numerical simulation is carried out to show the theoretical claims at the end.

This article designs the static and dynamic event-triggered control (ETC) and self-triggered control (STC) algorithms to achieve the semiglobal stabilization of discrete-time systems with input constraints. First, a novel static ETC algorithm based on the discrete-time parametric Lyapunov equation (DPLE) is designed. In order to further increase the interevent times (IETs), the corresponding dynamic ETC is designed. Next, both static and dynamic STC, where the next control law updates depend on the previous triggered states, are proposed to avoid monitoring the measurement errors. The proposed algorithms are not only capable of reducing the number of transmissions significantly but also build a very simple and clear relationship between the only design parameter and the nontrivial IET (NIET). This allows us to change regularly IETs by adjusting the design parameter so that the nontriviality of static and dynamic ETC and STC is guaranteed and a tradeoff between the IETs and the control performance can be easily found. Specifically, by exploring the properties of DPLE, the designed algorithms avoid the complex relationship between the nontrivial condition and the system matrices. Finally, the designed static and dynamic ETC and STC algorithms are applied to the design of the spacecraft rendezvous control system and their effectiveness is verified by simulation results.

In this paper, an interval observer-based fault diagnosis mechanism and an interval dynamic event-triggered robust fault-tolerant control strategy are proposed for uncertain nonlinear switched systems. Firstly, the interval observer design problem is transformed into a Sylvester equation solution problem by introducing the coordinate transformation method in the absence of actuator faults, and the corresponding interval observer design method is given. Secondly, based on the interval observer output, upper and lower bound estimates of the system output are constructed, and fault diagnosis is realized by monitoring whether the system output exceeds the preset bounds. In addition, an improved interval dynamic event triggered mechanism is proposed to optimize the utilization of communication and computational resources and reduce redundant information transmission. The mechanism incorporates interval estimation information and real-time residuals, which can effectively extend the triggering time interval while improving the fault detection performance. Based on the interval fault diagnosis results, a fault-tolerant control strategy based on the interval dynamic event triggered mechanism is proposed, and the conditions for asymptotic stabilization of the closed-loop system are given. Finally, a nonlinear model of a morphing aircraft system with variable wing curvature is used to verify the validity of the designed scheme. DOI: 10.61416/ceai.v28i1.9516

In this paper, the stability problem for event-triggered nonlinear control systems is addressed in the presence of stochastic denial of service (DoS) attacks on the communication network. Dynamic event-triggered control (DETC) and periodic event-triggered control (PETC) are considered under the stochastic attacks. The stochastic attacks are modeled by a stochastic hybrid timer and a logic variable which is used to identify whether the network is attacked or not. Then the entire closed-loop system can be modeled into the framework of stochastic hybrid systems. Uniform global asymptotic stability in probability is concluded for the resulting stochastic system by proving that the equilibrium set is uniformly globally stable in probability and each neighborhood of the equilibrium set is uniformly globally recurrent. A nonlinear system example is provided to illustrate the effectiveness of the proposed results.

Event-triggered adaptive neural network controller for uncertain nonlinear system

Dynamic event-triggered neuro-optimal control for uncertain nonlinear systems with unknown dead-zone constraint

This paper develops a new estimate-based dynamic event-triggered output feedback controller for networked control systems subject to nonlinear uncertainties. Specifically, based on the sampled-data, a discrete-time output feedback controller and a discrete-time dynamic event-triggering condition are proposed by the virtue of feedback domination technique. The proposed event-triggered control method is easy to implement in digital computers due to the form of discrete time. Under the proposed dynamic event-triggered control method, the selection regions of the sampling period and the scaling gain are explicitly given to guarantee the global practical/asymptotic stability of the closed-loop system. Finally, two examples are employed to verify the efficiency of the proposed dynamic event-triggered control approach.

Finite-time stabilization of linear systems by bounded event-triggered and self-triggered control

In this paper, a control scheme is presented for robotic manipulator by combining deterministic learning and event- triggered mechanism. Notice that the traditional adaptive neural control needs to re-adapt neural network (NN) weights even for performing the same control task, thereby result in the limited learning ability. To enhance the neural leaning ability, a dynamic learning controller is firstly constructed based on the radial basis function (RBF) NN, which has the ability to learn the knowledge of the unknown closed-loop system dynamics. By reusing the learned knowledge, the dynamic learning-based event-triggered control scheme is put forward to achieve a tradeoff between the network resource and the tracking performance. Specially, an easy-to-implemented event-triggered condition is designed by the Lyapunov technique due to the use of experience knowledge. The proposed scheme ensures that the tracking error converges to a small neighborhood of the origin, all the signals in the closed- loop system are bounded and meanwhile the communication resources are greatly reduced. A comparison simulation example is conducted to demonstrate the effectiveness and advantage of the proposed control scheme.

Most event-triggered controllers available nowadays are based on static state-feedback controllers. As in many control applications the full state is not available for feedback, it is the objective of this paper to propose event-triggered dynamical output-based controllers. The fact that the controller is based on output feedback instead of state feedback does not allow for straightforward extensions of existing event-triggering mechanisms if a minimum time between two subsequent events, the so-called `minimum inter-event time', has to be guaranteed. Therefore, we will propose an event-triggering mechanism that invokes execution of the control task when the difference between the measured output or the control input of the plant or controller, respectively, and its previously sampled value becomes `large' compared to its current value and an additional threshold. For such event-triggering mechanisms, we will study closed-loop stability and L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> -performance and provide bounds on the minimum inter-event time. In addition, we will model the event-triggered control system using impulsive systems, which truly describe the behaviour of the event-triggered control system. As a result, we can guarantee stability and performance for improved event-triggered controllers with larger minimum inter-event times than existing results in literature.

Chapter 8 - Event-triggered resilient platoon control: Distributed dynamic event-triggered secure model predictive control of vehicle platoon against DoS attacks