A novel compensation control method for heterogeneous multiagent systems under Denial-of-Service (DoS) attacks and transmission delays is investigated in this article. This control method has all the advantages of the cloud-based computation strategy, the adaptive event-triggered strategy, and the predictive control scheme. The adaptive event-triggering mechanism can adjust the event numbers adaptively, the predictive control can reduce or eliminate the negative effects brought out by both DoS attacks and transmission delays actively, while the cloud-based computation strategy can eliminate the negative effects completely as the same as there are no DoS attacks and transmission delays. Through the interval decomposition skill and the augmented system modeling method, the compensated geschlossenes system model is established. Moreover, the joint design for the feedback gain matrices and the event-triggered parameters is implemented. In the simulation part, five VTOL aircraft are used to demonstrate the theoretical results.

This article concerns observer-based consensus compensation control for heterogeneous networked multi-agent systems under both networked Denial of Service (DoS) attacks and transmission delays. We propose a control method that combines the observer-based adaptive event-triggered control and the observer-based cloud predictive control, which can not only reduce the network transmission burden, but also can compensate for the negative effects caused by DoS attacks and transmission delays completely. The consensus conditions, the observer and controller gain matrices and the event-triggering parameter matrices are all simultaneously derived by using the linear matrix inequality method.

In this paper, the event-based controller synthesis problem for networked control systems under the resilient event-triggering communication scheme (RETCS) and periodic denial-of-service (DoS) jamming attacks is studied. First, a new periodic RETCS is designed under the assumption that the DoS attacks imposed by power-constrained pulsewidth-modulated jammers are partially identified, that is, the period of the jammer and a uniform lower bound on the jammer's sleeping periods are known. Second, a new state error-dependent switched system model is constructed, including the impacts of the RETCS and DoS attacks. According to this new model, the exponential stability criteria are derived by using the piecewise Lyapunov functional. In these criteria, the relationship among DoS parameters, the triggering parameters, the sampling period, and the decay rate is quantitatively characterized. Then, a criterion is also proposed to obtain the explicit expressions of the triggering parameter and event-based state feedback controller gain simultaneously. Finally, the obtained theoretical results are verified by a satellite yaw-angles control system.

This paper focuses on a problem of event-triggered stabilization for a class of nonuniformly sampled neural-network-based control systems (NNBCSs). First, a new event-triggered data transmission mechanism is designed based on the nonperiodic sampled data. Different from the previous works, the proposed triggering scheme enables the NNBCSs design to enjoy the advantages of both nonuniform and event-triggered sampling schemes. Second, under the nonperiodic event-triggered data transmission scheme, the nonperiodic sampled-data three-layer fully connected feedforward neural-network (TLFCFFNN)-based event-triggered controller is constructed, and the resulting closed-loop TLFCFFNN-based event-triggered control system is modeled as a state delay system based on time-delay system modeling approach. Then, the stability criteria for the closed-loop system is formulated using Lyapunov-Krasovskii functional approach. Third, the sufficient conditions for the codesign of the TLFCFFNN-based controller and triggering parameters are given in terms of solvability of matrix inequalities to guarantee the asymptotical stability of the closed-loop system and an upper bound on the given cost function while reducing the updates of the controller. Finally, three numerical examples are provided to illustrate the effectiveness and benefits of the proposed results.

Super-resolution (SR) algorithms for video sequences with high resolution (HR) guide frames can provide outstanding performances. Non-local means (NLM) algorithm compares the similarity between a pixel and its neighbors. NLM replaces every pixel with a weighted average of its neighbors. The NLM based SR algorithm can super-resolve low resolution (LR) frames using the HR guide frames in the video sequence. However, the fixed decaying factor of NLM cannot satisfy regions of distinct characteristics in a LR frame. The fixed searching window fails to balance the requirements of low computational complexity and good SR images. Thus, we propose novel criteria for selecting the decaying factor and searching window adaptively. Bilateral adjacent HR frames are used to handle the occlusion problem. The experimental results verify the validity of the proposed method.

This paper focuses on a problem of event-based stabilization for a class of sampled-data neural-network-based control systems. By using a new discrete event-triggering mechanism, an event-based sampled-data three-layer fully connected feedforward neural-network-based controller is constructed. Compared with the conventional periodic sampled-data neural-network-based control in previous works, the main advantage of this paper is that the proposed event-based sampling and transmission scheme not only reduces the updating frequency of the controller, but also guarantees the asymptotical stability of the closed-loop system without dramatically degrading the overall system performance. Based on a discontinuous Lyapunov Krasovskii functional, a convex combination technique and the Wirtinger-based integral inequality, some new criteria are derived to guarantee the asymptotical stability and certain performance of closed-loop system in terms of linear matrix inequalities (LMIs). Based on the proposed criteria, a co-design method is presented to obtain the triggering parameter and the connection weights of the neural network simultaneously while ensuring a certain system performance. Finally, simulation results are provided to show the effectiveness and advantage of the proposed theoretical results.

This paper studies the observer-based event-triggered predictive control problem for networked control systems (NCSs). First, we propose a discrete event-triggered transmission scheme for the observer by introducing a quadratic event-triggering function. Then, based on the above scheme, a novel class of event-triggered predictive control algorithms on the controller node are designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. The closed-loop systems with the proposed observer-based event-triggered predictive control scheme for the analysis are established correspondingly. The design problems of the controller and the event-triggering parameter are discussed by using the linear matrix inequality (LMI) approach and the switching Lyapunov functional method. Finally, a practical example is employed to demonstrate the compensation effect for the communication delays with the proposed scheme in this paper.

This paper addresses the event-triggered predictive control problem for networked control systems (NCSs). First, we propose a discrete event-triggered transmission scheme on the sensor node by introducing a quadratic function. Then, based on the above scheme, a novel class of event-triggered predictive control algorithms on the controller node are designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. Two cases in terms of the communication delays are considered respectively. For the two cases, the closed-loop systems with the proposed event-triggered predictive control scheme for the analysis are established correspondingly. The co-design problems of the controller and event-triggering parameter are discussed by using the linear matrix inequality (LMI) approach and the (switching) Lyapunov functional method. Finally, a practical example is employed to demonstrate the effects of the proposed scheme.