A Novel Technique to Detect False Data Injection Attacks on Phasor Measurement Units

The power industry is in the process of grid modernization with the introduction of phasor measurement units (PMUs), advanced metering infrastructure (AMI), and other technologies. Although these technologies enable more reliable and efficient operation, the risk of cyber threats has increased, as evidenced by the recent blackouts in Ukraine and New York. One of these threats is false data injection attacks (FDIAs). Most of the FDIA literature focuses on the vulnerability of DC estimators and AC estimators to such attacks. This paper investigates FDIAs for PMU-based state estimation, where the PMUs are comparable. Several states can be manipulated by compromising one PMU through the channels of that PMU. A Phase Locking Value (PLV) technique was developed to detect FDIAs. The proposed approach is tested on the IEEE 14-bus and the IEEE 30-bus test systems under different scenarios using a Monte Carlo simulation where the PLV demonstrated an efficient performance.Peer reviewe

False Data Injection Detection for Phasor Measurement Units

Cyber-threats are becoming a big concern due to the potential severe consequences of such threats is false data injection (FDI) attacks where the measures data is manipulated such that the detection is unfeasible using traditional approaches. This work focuses on detecting FDIs for phasor measurement units where compromising one unit is sufficient for launching such attacks. In the proposed approach, moving averages and correlation are used along with machine learning algorithms to detect such attacks. The proposed approach is tested and validated using the IEEE 14-bus and the IEEE 30-bus test systems. The proposed performance was sufficient for detecting the location and attack instances under different scenarios and circumstances

Wearable metamaterial dual-polarized high isolation UWB MIMO Vivaldi antenna for 5G and satellite communications

A low-profile Multiple Input Multiple Output (MIMO) antenna showing dual polarization, low mutual coupling, and acceptable diversity gain is presented by this paper. The antenna introduces the requirements of fifth generation (5G) and the satellite communications. A horizontally (4.8–31 GHz) and vertically polarized (7.6–37 GHz) modified antipodal Vivaldi antennas are simulated, fabricated, and integrated, and then their characteristics are examined. An ultra-wideband (UWB) at working bandwidths of 3.7–3.85 GHz and 5–40 GHz are achieved. Low mutual coupling of less than −22 dB is achieved after loading the antenna with cross-curves, staircase meander line, and integration of the metamaterial elements. The antennas are designed on a denim textile substrate with = 1.4 and h= 0.5 mm. A conductive textile called ShieldIt is utilized as conductor with conductivity of 1.8 × 10⁴. After optimizing the proposed UWB-MIMO antenna’s characteristics, it is increased to four elements positioned at the four corners of a denim textile substrate to be employed as a UWB-MIMO antenna for handset communications, 5G, Ka and Ku band, and satellite communications (X-band). The proposed eight port UWB-MIMO antenna has a maximum gain of 10.7 dBi, 98% radiation efficiency, less than 0.01 ECC, and acceptable diversity gain. Afterwards, the eight-ports antenna performance is examined on a simulated real voxel hand and chest. Then, it is evaluated and compared on physical hand and chest of body. Evidently, the simulated and measured results show good agreement between them. The proposed UWB-MIMO antenna offers a compact and flexible design, which is suitably wearable for 5G and satellite communications applications

Design of a Hybrid Fault-Tolerant Control System for Air–Fuel Ratio Control of Internal Combustion Engines Using Genetic Algorithm and Higher-Order Sliding Mode Control

Fault-tolerant control systems (FTCS) are used in safety and critical applications to improve reliability and availability for sustained operation in fault situations. These systems may be used in process facilities to reduce significant production losses caused by irregular and unplanned equipment tripping. Internal combustion (IC) engines are widely used in the process sector, and efficient air–fuel ratio (AFR) regulation in the fuel system of these engines is critical for increasing engine efficiency, conserving fuel energy, and protecting the environment. In this paper, a hybrid fault-tolerant control system has been proposed, being a combination of two parts which are known as an active fault-tolerant control system and a passive fault-tolerant control system. The active part has been designed by using the genetic algorithm-based fault detection and isolation unit. This genetic algorithm provides estimated values to an engine control unit in case of a fault in any sensor. The passive system is designed by using the higher-order sliding mode control with an extra fuel actuator in the fuel supply line. The performance of the system was tested experimentally in MATLAB/Simulink environment. Based on the simulation results, the designed system can sustain the AFR despite sensor failures. A new method of managing the AFR of an IC engine has been demonstrated in this study, and it is highly capable, robust, reliable, and highly effective. A comparison with the existing works found in the literature also proves its superior performance. By inserting the fault in each sensor, it was clearly observed that proposed HFTCS was much better than the existing model as it was more fault-tolerant due to its ability to work in both online and offline modes. It also provided an exact value of 14.6 of AFR without any degradation

A Comparative Study of Design of Active Fault-Tolerant Control System for Air–Fuel Ratio Control of Internal Combustion Engine Using Particle Swarm Optimization, Genetic Algorithm, and Nonlinear Regression-Based Observer Model

In this article, three distinct strategies for designing an Active Fault-Tolerant Control System (AFTCS) for Air-Fuel Ratio (AFR) control of an Internal Combustion (IC) engine in a process plant to avoid engine shutdown, are presented. The proposed AFTCS employs a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a Nonlinear Regression (NLR)-based observer model in the Fault Detection and Isolation (FDI) unit for analytical redundancy. A comparison between these three proposed techniques is carried out to determine the least expensive and most accurate approach. The results show that the nonlinear regression produces highly accurate results by consuming very low computational power, and its response time is also very low as compared to GA and PSO. The results obtained show that NLR requires 99.6% and 93.1% less computational time for throttle and MAP estimation, respectively, by reducing the estimation error to as low as 0.01. The simulation of the proposed system is carried out in the MATLAB/Simulink environment. The results prove the superior fault tolerance performance for sensor faults of the AFR control system, especially for the Manifold Absolute Pressure (MAP) sensor in terms of less oscillatory response as compared to that reported in existing literature

Advanced Fault-Tolerant Anti-Surge Control System of Centrifugal Compressors for Sensor and Actuator Faults

Faults frequently occur in the sensors and actuators of process machines to cause shutdown and process interruption, thereby creating costly production loss. centrifugal compressors (CCs) are the most used equipment in process industries such as oil and gas, petrochemicals, and fertilizers. A compressor control system called an anti-surge control (ASC) system based on many critical sensors and actuators is used for the safe operation of CCs. In this paper, an advanced active fault-tolerant control system (AFTCS) has been proposed for sensor and actuator faults of the anti-surge control system of a centrifugal compressor. The AFTCS has been built with a dedicated fault detection and isolation (FDI) unit to detect and isolate the faulty part as well as replace the faulty value with the virtual redundant value from the observer model running in parallel with the other healthy sensors. The analytical redundancy is developed from the mathematical modeling of the sensors to provide estimated values to the controller in case the actual sensor fails. Dual hardware redundancy has been proposed for the anti-surge valve (ASV). The simulation results of the proposed Fault-tolerant control (FTC) for the ASC system in the experimentally validated CC HYSYS model reveal that the system continued to operate in the event of faults in the sensors and actuators maintaining system stability. The proposed FTC for the ASC system is novel in the literature and significant for the process industries to design a highly reliable compressor control system that would continue operation despite faults in the sensors and actuators, hence preventing costly production loss

Comparative Analysis of Flight Control Designs for Hypersonic Vehicles at Subsonic Speeds

Hypersonic vehicles are complex nonlinear systems with uncertain dynamics. Multiple designs of control systems for hypersonic vehicles based on nonlinear dynamic models have been applied with simulation results under high aircraft speed and altitude conditions. In contrast, the main contribution of this work is the design of three control systems: proportional-integral-derivative (PID), feedback linearization (FL, also known as dynamic inversion), and adaptive control (AC) for the flight operations of these vehicles at subsonic speeds and low altitude conditions. The complexity of the aerodynamic system is considered in the design of each control approach, in order to address robustness issues. The hypersonic vehicle model considered in this work has a v-tail and elevons, which makes the development of its flight control system more challenging to design. The longitudinal and lateral aerodynamics are decoupled as a means to control vehicle under specific flight conditions. Therefore, this work is focused on both longitudinal and lateral aerodynamics. The longitudinal aerodynamics (three degrees of freedom, or 3 DOF), which are divided into two subsystems: forward speed and flight-path angle. Two cases are considered for the lateral aerodynamics: fixed roll angle (5 DOF), and full stability analysis (6 DOF). The 5 DOF lateral aerodynamics are divided into three subsystems, for forward speed, flight path angle, and yaw angle, and the 6 DOF case includes a fourth subsystem for roll angle. Longitudinal and lateral aerodynamics contain uncertain parameters of three forces (drag, lift, and lateral) and three moments (pitch, roll, and yaw); further, the design of different control systems is necessary in order to achieve robust control and reduce the uncertainties. Different control design methodologies are implemented to provide asymptotic tracking of a desired forward speed (Vdes), desired flight-path angle (?des), desired roll angle (?des), and desired yaw angle (?des). The control approaches are compared in terms of longitudinal and lateral climbing flights and several performance measures, such as robustness. Based on the stability analysis, the FL and AC techniques are performed utilizing a Lyapunov function candidate of feedback closed-loop system. The simulation results of longitudinal and lateral aerodynamics determine the range of flight stability that is possible for this hypersonic vehicle model. Additionally, the simulation results for each control technique demonstrate the effectiveness of flight control inputs

Comparative Analysis of Flight Control Designs for Hypersonic Vehicles at Subsonic Speeds

Hypersonic vehicles are complex nonlinear systems with uncertain dynamics. Multiple designs of control systems for hypersonic vehicles based on nonlinear dynamic models have been applied with simulation results under high aircraft speed and altitude conditions. In contrast, the main contribution of this work is the design of three control systems: proportional-integral-derivative (PID), feedback linearization (FL, also known as dynamic inversion), and adaptive control (AC) for the flight operations of these vehicles at subsonic speeds and low altitude conditions. The complexity of the aerodynamic system is considered in the design of each control approach, in order to address robustness issues. The hypersonic vehicle model considered in this work has a v-tail and elevons, which makes the development of its flight control system more challenging to design. The longitudinal and lateral aerodynamics are decoupled as a means to control vehicle under specific flight conditions. Therefore, this work is focused on both longitudinal and lateral aerodynamics. The longitudinal aerodynamics (three degrees of freedom, or 3 DOF), which are divided into two subsystems: forward speed and flight-path angle. Two cases are considered for the lateral aerodynamics: fixed roll angle (5 DOF), and full stability analysis (6 DOF). The 5 DOF lateral aerodynamics are divided into three subsystems, for forward speed, flight path angle, and yaw angle, and the 6 DOF case includes a fourth subsystem for roll angle. Longitudinal and lateral aerodynamics contain uncertain parameters of three forces (drag, lift, and lateral) and three moments (pitch, roll, and yaw); further, the design of different control systems is necessary in order to achieve robust control and reduce the uncertainties. Different control design methodologies are implemented to provide asymptotic tracking of a desired forward speed (Vdes), desired flight-path angle (?des), desired roll angle (?des), and desired yaw angle (?des). The control approaches are compared in terms of longitudinal and lateral climbing flights and several performance measures, such as robustness. Based on the stability analysis, the FL and AC techniques are performed utilizing a Lyapunov function candidate of feedback closed-loop system. The simulation results of longitudinal and lateral aerodynamics determine the range of flight stability that is possible for this hypersonic vehicle model. Additionally, the simulation results for each control technique demonstrate the effectiveness of flight control inputs

Smart Grid Cyber Security Enhancement: Challenges and Solutions—A Review

The incorporation of communication technology with Smart Grid (SG) is proposed as an optimal solution to fulfill the requirements of the modern power system. A smart grid integrates multiple energy sources or microgrids and is supported by an extensive control and communication network using the Internet of Things (IoT) for a carbon-free, more reliable, and intelligent energy system. Along with many benefits, the system faces novel security challenges, data management, integration, and interoperability challenges. The advanced control and communication network in the smart grid is susceptible to cyber and cyber-physical threats. A lot of research has been done to improve the cyber security of the smart grid. This review aims to provide an overview of the types of cyber security threats present for smart grids with an insight into strategies to overcome the challenges. As the selection of techniques and technologies may vary according to the threats faced, therefore the adoption of researched methods is compared and discussed. As cyber-security is the greatest challenge in smart grid implementation, this review is beneficial during the planning and operation of smart grids for enhanced security

An Autonomous Vehicle Stability Control Using Active Fault-Tolerant Control Based on a Fuzzy Neural Network

Due to instability issues in autonomous vehicles, the risk of danger is increasing rapidly. These problems arise due to unwanted faults in the sensor or the actuator, which decrease vehicle efficiency. In this modern era of autonomous vehicles, the risk factor is also increased as the vehicles have become automatic, so there is a need for a fault-tolerant control system (FTCS) to avoid accidents and reduce the risk factors. This paper presents an active fault-tolerant control (AFTC) for autonomous vehicles with a fuzzy neural network that can autonomously identify any wheel speed problem to avoid instability issues in an autonomous vehicle. MATLAB/Simulink environment was used for simulation experiments and the results demonstrate the stable operation of the wheel speed sensors to avoid accidents in the event of faults in the sensor or actuator if the vehicle becomes unstable. The simulation results establish that the AFTC-based autonomous vehicle using a fuzzy neural network is a highly reliable solution to keep cars stable and avoid accidents. Active FTC and vehicle stability make the system more efficient and reliable, decreasing the chance of instability to a minimal point