A novel thruster fault detection (FD) strategy is investigated in this article for unmanned marine vehicles (UMVs) under external disturbances and aperiodic denial-of-service (DoS) attacks. To address the challenge of the inability to timely detect DoS attacks, the UMV under consideration and its corresponding filters are initially modeled under the framework of an asynchronous switched system. Then, sufficient conditions guaranteeing the system to be exponentially stable and with the prescribed performances are derived by leveraging the model-dependent average dwell time (MDADT) and piecewise Lyapunov functions (PLFs). Simultaneously, the lower bound of the tolerable sleep interval and the upper bound of the DoS attack interval are rigorously calculated. The design criteria of the FD filters are subsequently obtained through the employment of some decoupling techniques. Finally, the simulations on a UMV demonstrate the effectiveness of the proposed methods.

This paper mainly focuses on secure fault-tolerant control for nonlinear cyber-physical systems under the influence of multiple threats, i.e., sensor and actuator saturations, actuator fault, and intermittent denial-of-service attacks. A novel secure fault-tolerant control method is proposed within the Takagi-Sugeno fuzzy modeling framework, considering both saturation constraints and intermittent denial-of-service attacks, to ensure the secure performance of cyber-physical systems under multiple threats. By leveraging the advantages of the proposed method, the influence of outdated information caused by denial-of-service attacks is mitigated, and more precise state/fault estimations are obtained. Furthermore, the method guarantees the stability of both the estimation error system and the closed-loop system, even in the presence of intermittent denial-of-service attacks and saturation constraints. Finally, the effectiveness of this method is validated through experiment.

This paper investigates the problem of secure control for input saturated nonlinear cyber-physical systems (CPSs) subject to faults and multi-channel non-periodic denial-of-service (DoS) attacks. First, the model is reconstructed where the nonlinear characteristics can be described by using the Takagi-Sugeno (T-S) fuzzy modeling technique. Then, with the help of the sampling mechanism and the anti-windup compensator, a sampled data-based anti-windup fault-tolerant control scheme with membership function mismatch is proposed. This scheme effectively mitigates the impact of faults while alleviating performance degradation caused by input saturation. Furthermore, to address the challenges posed by multi-channel non-periodic DoS attacks, a resilient observer-based anti-windup secure fault-tolerant control strategy is further proposed to guarantee system stability. Finally, the simulation results are also given to verify the validity of the proposed method.

This article mainly focuses on the problem of observer-based adaptive event-triggered security fault-tolerant control (FTC) for attacked cyber-physical systems (CPSs). First, for the nonlinear characteristics in CPSs, the model is reconstructed based on the Takagi-Sugeno (T-S) fuzzy modeling technique. Then, a T-S fuzzy resilient observer is proposed to estimate the state as well as the actuator fault information. The proposed T-S fuzzy resilient observer proactively detects sensor transmission channels affected by dynamically changing denial-of-service (DoS) attacks, and proactively isolates contaminated data so as to reduce the impact of DoS attacks on the estimation effect. Based on the above content, an observer-based adaptive event-triggered security FTC scheme is proposed, which can ensure the stability of the CPSs and save the limited network resources between the controller and the actuator. Finally, simulation results are given to verify the effectiveness of the proposed scheme.

This article presents an event-triggered distributed secondary control with predictive compensation based on the model-free predictive control under Denial-of-Service (DoS) attacks in ac/dc-networked microgrids. First, models of ac/dc networked microgrids in both electric network and communication network are established. On this premise, event-triggered distributed secondary control is proposed to solve the problems of strong communication burden and low-power distribution accuracy. Besides, aiming at the impact of DoS attacks on distributed secondary control, a compensation algorithm based on model-free predictive control is designed to estimate the control variables when the DoS attack occurs, which can improve the control performance and maintain the stable operation without a specific system structure system. Then, the convergence of event-triggered distributed secondary control with the condition of whether DoS attacks happen are analyzed. Finally, the effectiveness of the proposed control is verified on the hardware-in-loop (HIL) simulation platform consisting of the RT-LAB simulator, MATLAB/Simulink simulation model, and DSP controller.

In order to estimate the unmeasurable velocities of dynamic positioning system of vessels quickly and consider reducing energy consumption, modelling errors and the ocean unknown disturbances, this paper proposes an optimal adaptive anti-disturbance constrains control scheme via finite-time velocity observer. Firstly, a fuzzy logic system is utilized to approximate modeling errors, and the finite-time velocity observer is established to obtain velocities quickly. Then, a disturbance observer is used to estimate the unknown disturbances. An auxiliary system is designed to compensate the effects of constrains. Based on the obtained velocities and disturbances information, the whole controller is composed of the adaptive anti-disturbance controller and the optimal compensation term designed by adaptive dynamic programming. It can be proved that all the signals in the closed-loop system are bounded. At Last, the simulation results verify the effectiveness of the proposed optimal control scheme.

This paper investigates the problem of attack tolerant state estimation for nonlinear Cyber-Physical Systems (CPSs). Firstly, a fuzzy system is employed to model the nonlinear CPS, and the system dynamics are re-described according to the working region, taking into account the effects of network attacks and multi-source disturbances. Inspired by previous interval observers and unknown input observers, an unknown input interval observer is proposed in this paper. The observer can isolate decoupled disturbances and the resulting interval error augment system is stable and robust to the bounded attack, with the caveat that the system matrix of the interval error augmentation system must also be non-negative. After some mathematical manipulation, these performances can be guaranteed by a set of linear matrix inequality (LMI) based solvable conditions. Finally, the effectiveness of the proposed method is verified through a set of experiments.

Aiming at the impact of multi time scales characteristics of different energy sources in the CCHP cluster on the controller period, in this paper, a two-time-scale consensus control based on the multi-rate sampling mechanism is proposed. Firstly, a multi-rate sampling mechanism that includes a buffer and a zero order holder is established to achieve the function of controller updating as soon as the buffer receives sampled data. Due to improved data utilization, the dynamic performance of the system is better compared to the single rate sampling mechanism. Then, considering that the heating/cooling energy produced in CCHP cluster is mainly used for adjusting the indoor temperature, and electricity power mainly supplies for electrical loads. Hence, room temperature, power generation cost, and the angular frequency measuring the stability of electricity power system are taken as control objectives. The proposed two-time-scale consensus control method considering the multi time scales characteristics and coupling characteristics between different energy sources in CCHP cluster, can ensure stable and economic operation of the system. Finally, the simulation results of a CCHP cluster containing 4 CCHP devices demonstrate the effectiveness of the proposed method.