This article investigates the problem of path following for the underactuated unmanned surface vehicles (USVs) subject to state constraints. A useful control algorithm is proposed by combining the backstepping technique, adaptive dynamic programming (ADP), and the event-triggered mechanism. The presented approach consists of three modules: guidance law, dynamic controller, and event triggering. First, to deal with the ``singularity'' problem, the guidance-based path-following (GBPF) principle is introduced in the guidance law loop. In contrast to the traditional barrier Lyapunov function (BLF) method, this article converts the USV's constraint model to a class of nonlinear systems without state constraints by introducing a nonlinear mapping. The control signal generated by the dynamic controller module consists of a backstepping-based feedforward control signal and an ADP-based approximate optimal feedback control signal. Therefore, the presented scheme can guarantee the approximate optimal performance. To approximate the cost function and its partial derivative, a critic neural network (NN) is constructed. By considering the event-triggered condition, the dynamic controller is further improved. Compared with traditional time-triggered control methods, the proposed approach can greatly reduce communication and computational burdens. This article proves that the closed-loop system is stable, and the simulation results and experimental validation are given to illustrate the effectiveness of the proposed approach.

In multiarea power systems, by preempting the transmission resources, denial-of-service (DoS) attacks may cause continuous packet losses in communication network and correspondingly make a performance degradation or even instability of the load frequency control (LFC) system. In this paper, a LFC scheme resilient to DoS attacks is developed. First, the dynamic boundary behaviors of data flow transmitted among multiple switches in normal no-DoS attack scenarios are described by using deterministic network calculus. Then, the analytic relationships among the upper transmission delay bound and key network parameters (e.g., packet size, forwarding rate, and hops) are deduced. Second, considering that the influences of bounded transmission delays on control instructions, the dynamics of closed-loop LFC systems are described as a series of subsystems with actual delays as the jumping decision variables. The established jumping model clearly demonstrates the dynamic evolution process of LFC systems under DoS attacks and stochastic delays. The $H_{\infty }$ -stabilization criteria considering parameter uncertainties are further deduced by using the Lyapunov theory and a constrained optimization algorithm is developed. Finally, case studies show the effectiveness of the proposed method.

This article investigates the load frequency control (LFC) problem for smart grids with denial-of-service (DoS) attacks via a novel event-triggered control method. In order to sustain the stable operation of the smart grids, a handshake logic-based event-triggered communication scheme is proposed. The targets of the designed controller are twofold. First, an event-triggered mechanism with a handshake logic-based concept is proposed to save network resources. In this triggering method, a handshake protocol is used to detect DoS attacks in the communication networks. Second, by employing Lyapunov stability theory, sufficient stabilization criteria ensuring the uncertain LFC systems being asymptotically stable are deduced. Based on these conditions, the corresponding state-feedback controller design method is given. Finally, a simulation of a two-area power system with electric vehicles is given as an example to substantiate the proposed method of this article.

This paper considers the model-reduction problem for continuous-time Takagi–Sugeno (T–S) fuzzy systems. Different from existing full-frequency methods, a finite-frequency model-reduction method is proposed in this paper. The proposed method can get a better approximation performance when input signals belong to a finite-frequency domain. To this end, a finite-frequency $H_\infty$ performance index is first defined. Then, a sufficient finite-frequency performance analysis condition is derived by the aid of Parseval's theorem and quadratic functions. Based on this condition and projection lemma, three model-reduction algorithms for T–S fuzzy systems with input signals in low-frequency, middle-frequency, and high-frequency domain are obtained, respectively. Finally, an example is given to illustrate the effectiveness of the proposed method.

BACKGROUND:Oral anticoagulants (OACs) such as warfarin and non-VKA oral anticoagulants (NOACs) have been recommended for patients with atrial fibrillation (AF) who are at risk for stroke. Whether NOACs have a higher persistence than warfarin is still...