Smart power grids are being enhanced by adding a communication infrastructure to improve their reliability, sustainability, and efficiency. Despite all of these significant advantages, open architecture connectivity renders the systems' vulnerability range cyberattacks. This article proposes novel resilient control system for load frequency (LFC) under false data injection (FDI) attacks. It is common use encryption in transfer links as first layer defending mechanism; here, we propose second...

Faults and failures in the system components are two main reasons for instability degradation control performance. In recent decades, fault-tolerant (FTC) approaches have been introduced to improve resiliency of systems against faults failures. general, FTC techniques classified into active passive approaches. This paper reviews fault failure causes discusses latest solutions that make resilient.The achievements detection isolation (FDI) designs investigated. Furthermore, a thorough...

Attack detection problems in industrial control systems (ICSs) are commonly known as a network traffic monitoring scheme for detecting abnormal activities. However, network-based intrusion system can be deceived by attackers that imitate the system’s normal activity. In this work, we proposed novel solution to problem based on measurement data supervisory and acquisition (SCADA) system. The approach is called (MIDS), which enables detect any activity even if attacker tries conceal it layer....

In networked control systems (NCS), agents participating in a network share their data with others to work together. When data, they can naturally expose the NCS layers of faults and cyber-attacks, which contribute propagation error from one agent/area another within system. One common type attack adversaries corrupt information is called false injection (FDI) attack. This article proposes scheme, enables detect mitigate FDI attacks and, at same time, compensate for measurement noise process...

Faults in aircraft actuators can cause serious issues safety. Due to the autonomous nature of unmanned aerial vehicles (UAVs), faults lead more problems these systems. In this paper, a new active fault tolerant control (FTC) system design for an UAV is presented. The proposed uses neural network adaptive structure detection and isolation (FDI), then, FDI signal combined with nonlinear dynamic inversion technique used compensate actuators. scheme detects isolates real-time without need...

A resilient and secure control system should be designed to as safe robust possible in face of different types attacks such fault data injection (FDI) attacks; thus, nowadays, the designers also consider probable their design from beginning. For this reason, detection intentional faults cyber-attacks attracts a great concern among researchers. This issue plays role safety unmanned aerial vehicles (UAVs) due need continuous supervision these systems. In order have cyber-attack tolerant (CAT)...

A network of vehicular cyber-physical systems (VCPSs) can use wireless communications to interact with each other and the surrounding environment improve transportation safety, mobility, sustainability. However, cloud-oriented architectures are vulnerable cyber attacks, which may endanger passenger pedestrian safety privacy, cause severe property damage. For instance, a hacker message falsification attack affect functionality particular application in platoon VCPSs. In this paper, neural...

A continuous controller is developed for a centralized network control system (NCS), which composed of agents with nonlinear dynamics subject to time-delay-switch (TDS) attack and additive disturbances. Since the state tracking error unmeasurable during TDS attacks, controllers cannot use coordinate NCS. Therefore, novel signal designed address this unique challenge enable NCS achieve formation objective. Furthermore, mitigation strategy developed, uses both learning- model-based approaches...

Alzheimer's disease (AD) is the most prevalent neurodegenerative that progressive and can be characterized mostly by neuronal atrophy, amyloid deposition, accompanied cognition, behavioral psychological deficits. In recent decade, a variety of machine learning algorithms have been explored used for AD diagnosis, focusing on its subtle prodromal stage mild cognitive impairment (MCI) to assess essential features characterize early manifestation plan treatment. However, diagnosis MCI (EMCI)...

A novel adaptive neural network-based fault-tolerant control scheme is proposed for six degree-of-freedom nonlinear helicopter dynamic. The approach can detect and mitigate actuators sensors’ faults in real time. An observer-based on network (NN) extended Kalman filter (EKF) designed, which incorporates the helicopter’s dynamic model to navigation sensors. Based detected faults, an active controller, including three loops of inversion, designed compensate occurred simulation results showed...

This paper introduces a novel controller design for pressure control in the proton exchange membrane (PEM) fuel cells. The proposed can system under fault/failure of actuators. introduced uses an artificial neural network online fault detection and isolation valves PEM cell (PEMFC). We designed nonlinear based on feedback linearization technique to compensate effects real time. also investigated stability Lyapunov theory. simulation hardware loop results clearly show that active...

The False Data Injection (FDI) attack on Load Frequency Control (LFC) caused by the adversary can destabilize power system. This could cause potential economic and life damages. Therefore, real-time detection of FDI attacks is necessary essential to compensate negative effects such attacks. paper presents a neural network-based (NND) approach estimate detect injected sensing loop (SL) A two-area distributed system considered as our case study demonstrate effectiveness NND strategy....

Advanced driver assistance systems (ADASs) enhance transportation safety and mobility, reduce impacts on the environment economical costs, through decreasing errors. One of main features ADASs is cruise control system that maintains driver's desired speed without intervention from driver. Adaptive (ACC) adjust vehicle's to maintain a safe following distance vehicle in front. Adding vehicle-to-vehicle vehicle-to-infrastructure communications (V2X) ACC systems, result cooperative adaptive...

<div class="section abstract"><div class="htmlview paragraph">This paper explores the role and challenges of Artificial Intelligence (AI) algorithms, specifically AI-based software elements, in autonomous driving systems. These AI systems are fundamental executing real-time critical functions complex high-dimensional environments. They handle vital tasks like multi-modal perception, cognition, decision-making such as motion planning, lane keeping, emergency braking. A primary...

The occurrence of faults and failures in flight control systems unmanned aerial vehicles (UAVs) can destabilize the system which could cause potential economic life losses. Therefore, it's necessary to detect attacks real time modify based on occurred fault. In this paper, a neural network-based fault detection (NNFD) approach is introduced estimate false data injection (FDI) sensor quadrotor time. An selected as our case study demonstrate effectiveness proposed NFDD strategy. simulation...

A novel active resilient control system is developed for distributed power systems (DPSs) under false data injection (FDI) attacks, and faults. The proposed works based on a new anomaly detection (AD) design which consists of Luenberger observer an artificial neural network (ANN). ANN structure by Extended Kalman filter (EKF) to improve the ability online AD in system. Based feedback received from system, controller will be designed, eliminates need reconfiguration. resiliency against FDI...

Alzheimer‘s disease (AD) is a neurodegenerative which progressive and can be described by amyloid deposition, neuronal atrophy. In this study, support vector machine (SVM) approach with radial basis function (RBF) has been proposed in order to detect the Alzheimer's its early stage using multiple modalities, including positron emission tomography (PET), magnetic resonance imaging (MRI), standard neuropsychological test scores. A total number of 896 participants from Disease Neuroimaging...