Event-triggered Control Policy Research Articles

Mitigating delay due to capacity drop near freeway bottlenecks: Zones of influence of connected vehicles.

We present a novel perspective on how connected vehicles can reduce total vehicular delay arising due to the capacity drop phenomenon observed at fixed freeway bottlenecks. We analytically determine spatial regions upstream of the bottleneck, called zones of influence, where a pair of connected vehicles can use an event-triggered control policy to positively influence a measurable traffic macrostate, e.g., the total vehicular delay at bottlenecks. These analytical expressions are also able to determine the boundaries (called null and event horizons) of these spatial extents, outside of which a connected vehicle cannot positively influence the traffic macrostate. These concepts can help ensure that information is disseminated to connected vehicles in only those spatial regions where it can be used to positively impact traffic macrostates. Some scenarios examined in this study indicate that communication between connected vehicles may be required over a span of several kilometers to positively impact traffic flow and mitigate delays arising due to the capacity drop phenomenon.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

Abstract The objective of this paper is to develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network. It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network. For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed. In an event-triggered system, when an error signal exceeding a specified time-varying threshold it indicates the occurrence of a typical event. The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed. Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs. A simulation example is finally used to verify the effectiveness of such a control strategy can enhance the system performance.

Fully Distributed Event-Triggered Vehicular Platooning With Actuator Uncertainties

The goal of this paper is to design a fully distributed event-triggered control policy with intermittent communication to reach leader-follower consensus of vehicular platoons with nonzero leader's input and actuator uncertainties. The time-dependent event-triggered condition in a fully distributed manner is proposed for checking the necessary data transmission time. Meanwhile, a distributed control law based on estimated state is developed when the event-triggered condition is violated, which ensures the platoon can reach bounded consensus with an exponential convergence rate. Compared with existing related results, the fully distributed event-triggered mechanism is independent of any global information or leader's information. Moreover, Zeno behavior can be strictly ruled out for each vehicle. Finally, the effectiveness of the proposed event-triggered control policy is validated by numerical examples.

Event-triggered design for discrete-time nonlinear systems with control constraints

In order to solve the constrained-input problem and reduce the computing resources, a novel event-triggered optimal control method is proposed for a class of discrete-time nonlinear systems. In the proposed method, the event-triggered control policy is applied to the globalized dual heuristic dynamic programming (GDHP) algorithm. Compared with the traditional adaptive dynamic programming (ADP) control, the event-triggered GDHP control can reduce the computation while ensuring the system performance. In this paper, a non-quadratic function is given to code the control constraints and the trigger condition with the stability analysis is provided. Neural networks (NN) are constructed in the GDHP structure, where the model network is designed to identify the unknown nonlinear system, the critic network is used to learn the cost function and its partial derivative, and the action network is designed to obtain the approximate optimal control law. Three simulation examples are presented to demonstrate the performance of the proposed event-triggered design for constrained discrete-time nonlinear systems.

Event-Based Prescribed Performance Control for Dynamic Positioning Vessels

This brief investigates the problem of trajectory tracking control for dynamic positioning vessels under unknown and time-varying sea loads. A novel event-based prescribed performance control (PPC) scheme is proposed to address this problem. Firstly, an integral disturbance observer (IDO) is introduced to estimate the sea loads, and a new-type performance function (PF), which has advantages of flexible shape and appointed-time convergence, is proposed to form the funnel envelops for the trajectory tracking errors. Subsequently, by employing the IDO and the new-type PF, a dynamic event-triggered control policy is designed in the PPC framework to achieve the assigned trajectory tracking mission in an appointed-time with guaranteed performance bounds and less operating frequency of the actuator. The salient feature of the derived controller is that it can achieve a trade-off between the tracking performance and actuators’ operating frequency in a well-balanced way, which is of great importance for practical engineering applications. Finally, simulation results are given to show the effectiveness of the proposed method.

Event- and self-triggered control of attitude coordination to multi-spacecraft system

PurposeThe purpose of this paper is to investigate the attitude cooperation control of multi-spacecraft with in-continuous communication.Design/methodology/approachA decentralized state-irrelevant event-triggered control policy is proposed to reduce control updating frequency and further achieve in-continuous communication by introducing a self-triggered mechanism.FindingsEach spacecraft transmits data independently, without the requirement for the whole system to communicate simultaneously. The local predictions and self-triggered mechanism avoid continuous monitoring of the triggering condition.Research limitations/implicationsThis investigation is suitable for small Euler angle conditions.Practical implicationsThe control policy based on event-triggered communication can provide potential solutions for saving communication resources.Originality/valueThis investigation uses event- and self-triggered policy to achieve in-communication for the multi-spacecraft system.

Model-Based Periodic Event-Triggered Control Strategy to Stabilize a Scalar Nonlinear System

This article focuses on the problem of stabilizing a scalar continuous-time nonlinear system under bounded network delay and process noise. In order to save the feedback network's bandwidth, a model-based periodic event-triggered control policy is utilized to maintain longer intersampling intervals, which are at least as long as the sampling period of periodic policies. Furthermore, the event-triggering condition is only checked intermittently at fixed time instants, i.e., the sampling time instants. Without acknowledgment (ACK), the updating of nominal models at the sensor and at the controller are asynchronous. The two cases, where the network delay is either less than the sampling period or larger than the sampling period, are investigated. In comparison with periodic sampling methods, our scheme can make full use of the received data packets, particularly their sampling time instant information, which yields a lower occupied bit rate while guaranteeing the desired input-to-state stability. Note that the obtained bit rate conditions are only related to the Lipschitz parameter, the bound of network delay, the number of quantization bits, and the sampling period. The bounded process noise will not incur any increase of the stabilizing bit rate under the proposed strategy.

Adaptive Critic Learning and Experience Replay for Decentralized Event-Triggered Control of Nonlinear Interconnected Systems

In this paper, we develop a decentralized event-triggered control (ETC) strategy for a class of nonlinear systems with uncertain interconnections. To begin with, we show that the decentralized ETC policy for the whole system can be represented by a group of optimal ETC laws of auxiliary subsystems. Then, under the framework of adaptive critic learning, we construct the critic networks to solve the event-triggered Hamilton–Jacobi–Bellman equations related to these optimal ETC laws. The weight vectors used in the critic networks are updated by using the gradient descent approach and the experience replay (ER) technique together. With the aid of the ER technique, we can conquer the difficulty arising in the persistence of excitation condition. Meanwhile, by using classic Lyapunov approaches, we prove that the estimated weight vectors used in the critic networks are uniformly ultimately bounded. Moreover, we demonstrate that the obtained decentralized ETC can force the overall system to be asymptotically stable. Finally, we present an interconnected nonlinear plant to validate the proposed decentralized ETC scheme.

Consistent Dynamic Event-Triggered Policies for Linear Quadratic Control

We say that an event-triggered control policy is consistent if it achieves a better closed-loop performance than that of traditional periodic control for the same average transmission rate and does not generate transmissions in the absence of disturbances. In this paper, we propose a class of dynamic event-triggered control strategies that satisfy these two conditions for any linear system when performance is measured by an average quadratic cost. A numerical example shows that these conditions may not be necessarily satisfied by a well-known event-triggered policy for which transmissions are triggered if the Euclidean norm of the error between the system's state and a state prediction exceeds a given threshold.

Event-Triggered $H_\infty $ Control for Continuous-Time Nonlinear System via Concurrent Learning

In this paper, the ${H}_{\infty }$ optimal control problem for a class of continuous-time nonlinear systems is investigated using event-triggered method. First, the ${H}_{\infty }$ optimal control problem is formulated as a two-player zero-sum (ZS) differential game. Then, an adaptive triggering condition is derived for the ZS game with an event-triggered control policy and a time-triggered disturbance policy. The event-triggered controller is updated only when the triggering condition is not satisfied. Therefore, the communication between the plant and the controller is reduced. Furthermore, a positive lower bound on the minimal intersample time is provided to avoid Zeno behavior. For implementation purpose, the event-triggered concurrent learning algorithm is proposed, where only one critic neural network (NN) is used to approximate the value function, the control policy and the disturbance policy. During the learning process, the traditional persistence of excitation condition is relaxed using the recorded data and instantaneous data together. Meanwhile, the stability of closed-loop system and the uniform ultimate boundedness (UUB) of the critic NN’s parameters are proved by using Lyapunov technique. Finally, simulation results verify the feasibility to the ZS game and the corresponding ${H}_{\infty }$ control problem.

Sampled-data output feedback control based on a new event-triggered control scheme

In this paper, a new event-triggered control (ETC) scheme is proposed to investigate the observer-based output feedback control problems. To reduce the usage of communication resources, the control input is designed as a specific time-varying signal between two consecutive event-triggering instants, which is different from the general ETC methods. For the continuous-time event detection case, it is shown that the obtained lower bound of the minimum inter-event interval is not smaller than the one using the existing method. In addition, a novel discrete-time event detection scheme and the corresponding ETC policy based on the sampling output is proposed. Employing the stability analysis method for the time-delay system, a sufficient condition on the existence of an observer-based controller is presented. Finally, the simulation results are given to show that the proposed ETC scheme is beneficial to further reduce the frequency of the communication between sensors and the control unit.