Performance-Based Hierarchical Fault-Tolerant Control for Closed-Loop Systems With Multiplicative Faults: A Data-Driven Design Method.

Fault-tolerant control (FTC) is vital for the safety and reliability of automatic systems. Most of the existing FTC methods are developed for open-loop systems subject to additive faults, regardless of the widely present control loops and multiplicative faults within systems. In this article, a performance-based FTC strategy is proposed for the closed-loop systems with multiplicative faults.

A Sampled-Data-Based Secure Control Approach for Networked Control Systems Under Random DoS Attacks.

This article aims to analyze H stability of a class of networked control systems (NCSs) under random denial of service (DoS) attacks and design a sampled-data-based state feedback security controller to mitigate the influence of attacks. Different from the existing random attacks, the information about the maximum duration time of DoS attacks can be captured by introducing a predesigned logical processor. Then, based on the periodic sampling technique, the probability of attack occurrence and the resultant number of maximum allowable consecutive packet dropouts can be calculated, which is quite significant to investigating the security problem of NCSs.

Important-Data-Based DoS Attack Mechanism and Resilient H Filter Design for Networked T-S Fuzzy Systems.

This article is concerned with the security problems for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous premise constraints. The primary objective of this article is twofold. First, a novel important-data-based (IDB) denial-of-service (DoS) attack mechanism is proposed from the perspective of the adversary for the first time to reinforce the destructive effect of the DoS attacks.

Quasi-Consensus Control for Stochastic Multiagent Systems: When Energy Harvesting Constraints Meet Multimodal FDI Attacks.

In this article, the quasi-consensus control problem is investigated for a class of stochastic nonlinear time-varying multiagent systems (MASs). The innovation points of this research can be highlighted as follows: first of all, the dynamics of the plant are stochastic, nonlinear, and time varying, which resembles the natural systems in practice closely. Meanwhile, an energy harvesting protocol is put forward to collect adequate energy from the external environment.

Codesign of FDI Attacks Detection, Isolation, and Mitigation for Complex Microgrid Systems: An HBF-NN-Based Approach.

The primary purpose of this article is to design an intelligent false data injection (FDI) attacks detection, isolation, and mitigation scheme for a class of complex microgrid systems with electric vehicles (EVs). First, a networked microgrid with an EV model is well established, which takes load disturbance, wind generation fluctuation, and FDI attacks into account so as to truly reflect the operation process of the complex system. Then, an intelligent hyper basis function neural network (HBF-NN) observer is designed to accurately estimate the state of the microgrids, learn, and reconstruct the possible attack signal online.

Event-based fuzzy resilient control of nonlinear DC Microgrids under denial-of-service attacks.

This paper focuses on designing an event-triggered fuzzy resilient controller for networked nonlinear DC microgrid (MG) with constant power loads (CPLs) in the presence of denial-of-service (DoS) attacks. First, an attack-resilient event-triggered communication scheme is introduced to reduce the communication overhead of the DC MG while achieving the desired performance despite the presence of the DoS attacks. Second, the nonlinear event-triggered DC MG system with CPLs is modeled as a T-S fuzzy system with artificial delay through the sector nonlinearity approach combined with time-delay system modeling method.

Histological image color normalization using a skewed normal distribution mixed model.

Color variation between histological images may influence the performance of computer-aided histological image analysis. Therefore, among the most essential and challenging tasks in histological image analysis are the reduction of the color variation between images and the preservation of the histological information contained in the images. In recent years, many methods have been introduced with respect to the color normalization of histological images.

Chance-Constrained H State Estimation for Recursive Neural Networks Under Deception Attacks and Energy Constraints: The Finite-Horizon Case.

In this article, the chance-constrained H state estimation problem is investigated for a class of time-varying neural networks subject to measurements degradation and randomly occurring deception attacks. A novel energy-constrained deception attack model is proposed, in which both the occurrence of the attack and the selection of released faked packet are random and the energy of the deception attack is introduced, calculated, and analyzed quantitatively. The main purpose of the addressed problem is to design an H estimator such that the prefixed probabilistic constraints of the system error dynamics are satisfied and the H performance is also ensured.

Dynamic Event-Triggered Output Feedback Control for Networked Systems Subject to Multiple Cyber Attacks.

This article is concerned with the problem of the H output feedback control for a class of event-triggered networked systems subject to multiple cyber attacks. Two dynamic event-triggered generators are equipped at sensor and observer sides, respectively, to lower the frequency of unnecessary data transmission. The sensor-to-observer (STO) channel and observer-to-controller (OTC) channel are subject to deception attacks and Denial-of-Service (DoS) attacks, respectively.

Co-Design of Dynamic Event-Triggered Communication Scheme and Resilient Observer-Based Control Under Aperiodic DoS Attacks.

This article is concerned with the problem of observer-based dynamic event-triggered control for a networked control system (NCS) under a class of power-constrained denial-of-service (DoS) attacks that aim at impeding the network communication from time to time. First, by carefully modeling such DoS attacks as aperiodic pulse-width-modulated (PWM) jamming signals, a switching observer, adapting to the DoS attacks, is delicately constructed to deal with the unavailability of full-state information. Second, to economize the limited bandwidth resources, a dynamic event-triggered communication scheme is designed under the aperiodic DoS jamming attacks, whose duration and frequency are assumed to be restricted.

Memory-Based Event-Triggering H Load Frequency Control for Power Systems Under Deception Attacks.

This article proposes a memory-based event-triggering H load frequency control (LFC) method for power systems through a bandwidth-constrained open network. To overcome the bandwidth constraint, a memory-based event-triggered scheme (METS) is first proposed to reduce the number of transmitted packets. Compared with the existing memoryless event-triggered schemes, the proposed METS has the advantage to utilize series of the latest released signals.

Finite-horizon tracking control for a class of stochastic systems subject to input constraints and hybrid cyber attacks.

This paper is concerned with the probabilistic-constrained finite-horizon tracking control problem for a class of stochastic systems subject to randomly occurring hybrid cyber attacks and input constraints. Both the randomly occurring denial-of-service (DOS) attacks and randomly occurring deception attacks are considered in an unified framework. The purpose of the current study is to design an observer-based tracking controller such that: over a finite horizon, (1) the variance of the estimation error is less than certain bound at each time step, (2) the probability of the tracking error falling in certain region should larger than a specified value and the region is minimized at each time step.

Event-based finite-time state estimation for Markovian jump systems with quantizations and randomly occurring nonlinear perturbations.

This paper is concerned with finite-time state estimation for Markovian jump systems with quantizations and randomly occurring nonlinearities under event-triggered scheme. The event triggered scheme and the quantization effects are used to reduce the data transmission and ease the network bandwidth burden. The randomly occurring nonlinearities are taken into account, which are governed by a Bernoulli distributed stochastic sequence.

Delay-distribution-dependent H state estimation for delayed neural networks with (x,v)-dependent noises and fading channels.

This paper deals with the H state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying stochastic delay takes values on certain intervals with known probability distributions. The system measurement is transmitted through fading channels described by the Rice fading model.

Event-triggered reliable H filter design for networked systems with multiple sensor distortions: A probabilistic partition approach.

In this paper, the problem of event-triggered reliable H filtering for networked systems with multiple sensor distortions is investigated. The interval of sensor distortion in each channel is partitioned several segments. By introducing a set of rand variables, the model of multiple sensor distortions with their information of probability distribution in each segment is established, which is more general than the one in open results.

Delay-distribution-dependent stability and stabilization of T-S fuzzy systems with probabilistic interval delay.

In this paper, we are concerned with the problem of stability analysis and stabilization control design for Takagi-Sugeno (T-S) fuzzy systems with probabilistic interval delay. By employing the information of probability distribution of the time delay, the original system is transformed into a T-S fuzzy model with stochastic parameter matrices. Based on the new type of T-S fuzzy model, the delay-distribution-dependent criteria for the mean-square exponential stability of the considered systems are derived by using the Lyapunov-Krasovskii functional method, parallel distributed compensation approach, and the convexity of some matrix equations.