Event-triggered control over unreliable networks subject to jamming attacks

In this paper, the periodic event-triggered suboptimal control (PETSOC) method is developed for continuous-time linear systems. Different from event-triggered control, where the triggering condition is monitored continuously, the developed PETSOC method only verifies the triggering condition periodically at sampling instants, which further reduces computational resources. First, the control gain of the PETSOC is designed based on the algebraic Riccati equation. Subsequently, the periodic event-triggering condition is proposed for the suboptimal control method, which is only verified at sampling instants periodically. The sampling period is determined and analyzed based on the continuous form of the triggering condition. Moreover, the stability and the performance upper bound of the closed-loop system with the PETSOC are proved. Finally, the effectiveness of the developed PETSOC is validated through simulation on an unstable batch reactor.

Event-triggered robust cooperative output regulation for a class of linear multi-agent systems with an unknown exosystem

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

Finite-time event-triggered consensus control for high-speed train with gradient resistance

Distributed event-triggered fuzzy control for nonlinear interconnected systems

Derivative-based event-triggered control for networked systems with quantization

In this paper, a dual-channel event-triggered control (ETC) protocol with a state estimator is designed in multi-agent systems with switching topologies under denial-of-service attacks. Firstly, an ETC protocol and a dynamic ETC protocol are designed in the communication channel and the controller–actuator channel, respectively. Different from the traditional single-channel ETC, the dual-channel ETC is designed to further save resources. Second, an estimator is introduced to avoid continuous communication between agents. The sufficient conditions for realizing consensus are obtained under denial-of-service attacks. Moreover, due to the unstable communication topology of multi-agent systems, we designed a distributed controller based on switching topologies. Finally, the feasibility of the proposed method is verified through numerical simulations.

This paper presents a method of reducing data communication burden in multi area load frequency control. An aperiodic event-triggered based control approach has been adopted to reduce the communication bandwidth requirements and governor operations. The control law is computed and actuated only when a pre-defined output dependent event condition is satisfied. The triggering condition in the previously reported works, depends on system states or outputs of all areas which is generally not available in an area control center of a real power system. Therefore a distributed event-triggered load frequency control has been proposed where the triggering condition in an area control center depends on output information of that particular area. A passivity based approach is adopted to ensure the system stability analytically and to derive the event triggering condition. Performance of the proposed controller was shown in terms of RMS error of frequency, tie line deviations and the reduction in communication burden for continuous load change, step load change and plant model variations in a two area test system.

This paper investigates the problem of event-triggered networked predictive control for systems with data loss. An event-triggered networked predictive control system is proposed. Based on predictive control model, a data loss compensation strategy is presented and an extended event-triggered transmission mechanism is developed. The closed-loop event-triggered predictive control system is described as a switched system and sufficient closed-loop stability conditions related to event-triggered mechanism are established. Under the event-triggered networked predictive control scheme, the consumption of the communication resources is reduced. Finally, an example is provided to illustrate the effectiveness of the proposed method.

In this paper, an approximation-based event-triggered model predictive control (AETMPC) strategy is proposed to implement event-triggered model predictive control for continuous-time constrained nonlinear systems under the digital platform. In the AETMPC strategy, both of the optimal control problem (OCP) and the triggering conditions are defined in a discrete-time manner based on approximate discrete-time models, while the plant under control is continuous time. In doing so, sensing load is alleviated because the triggering condition does not need to be checked continuously, and the computation of the OCP is simpler since which is calculated in the discrete-time framework. Meanwhile, robust constraints are satisfied in a continuous-time sense by taking inter-sampling behavior into consideration, and a novel constraint tightening approach is presented accordingly. Furthermore, the feasibility of the AETMPC strategy is analyzed and the associated stability of the overall system is established. Finally, this strategy is validated by a numerical example.

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.

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.

Based on an event-triggered control strategy, the stabilization of a linear system with disturbance is the purpose of this article. In this article, we first introduce a newfangled event-triggered control with a linear diffusive term and discontinuous sign term. Then, a class of event-triggered conditions, whose threshold contains a constant term and a sampled state term, is provided for guaranteeing the stability of a disturbed linear system. The event could be directly triggered to change the control information by violating the event-triggered condition when packet losses during control information transmission are defaulting. This means that event-triggered control can markedly economize on resource waste and communication cost. In addition, the interexecution time, which is determined by the event-triggered condition, is proved to have a uniform positive lower bound to guarantee that Zeno behavior does not occur. In the presence of packet losses, we estimate the maximum allowable number of successive packet losses to maintain the desired performance of the system. Finally, the validity of the theoretical results is substantiated by an example.

This paper discusses the distributed output optimization problem for a group of linear multi-agent systems via event-triggered control. In this problem, each agent has an individual objective function and is required to reach the minimal solution of the sum of these objective functions. By inserting a dynamic compensator to generate this optimal point, we develop a novel distributed event-triggered controller to solve this problem, where the control inputs only update at some time instants specified by us. An example is given to verify the effectiveness of our designs.

Smart mobility, with its urban transportation services ranging from real-time traffic control to cooperative vehicle infrastructure systems, is becoming increasingly critical in smart cities. These smart mobility services thus need to be very well protected against a variety of security threats, such as intrusion, jamming, and Sybil attacks. One of the frequently cited attacks in smart mobility is the jamming attack. In order to detect the jamming attacks, different anti-jamming applications have been developed to reduce the impact of malicious jamming attacks. One important step in anti-jamming detection is to cluster the vehicular data. However, it is usually very time-consuming to detect the jamming attacks that may affect the safety of roads and vehicle communication in real-time. Therefore, this paper proposes an efficient big data clustering model, coresets-based clustering, to support the real-time detection of jamming attacks. We validate the model efficiency and applicability in the context of a typical smart mobility system: Vehicular Ad-hoc Network, known as VANET.