The need to create more viable soft sensors is increasing in tandem with the growing interest in soft robots. Several sensing methods, like capacitive stretch sensing and intrinsic capacitive self-sensing, have proven to be useful when controlling soft electro-hydraulic actuators, but are still problematic. This is due to challenges around high-voltage electronic interference or the inability to accurately sense the actuator at higher actuation frequencies. These issues are compounded when trying to sense and control the movement of a multiactuator system. To address these shortcomings, we describe a two-part magnetic sensing mechanism to measure the changes in displacement of an electro-hydraulic (HASEL) actuator. Our magnetic sensing mechanism can achieve high accuracy and precision for the HASEL actuator displacement range, and accurately tracks motion at actuation frequencies up to 30 Hz, while being robust to changes in ambient temperature and relative humidity. The high accuracy of the magnetic sensing mechanism is also further emphasized in the gripper demonstration. Using this sensing mechanism, we can detect submillimeter difference in the diameters of three tomatoes. Finally, we successfully perform closed-loop control of one folded HASEL actuator using the sensor, which is then scaled into a deformable tilting platform of six units (one HASEL actuator and one sensor) that control a desired end effector position in 3D space. This work demonstrates the first instance of sensing electro-hydraulic deformation using a magnetic sensing mechanism. The ability to more accurately and precisely sense and control HASEL actuators and similar soft actuators is necessary to improve the abilities of soft, robotic platforms.

In this work, we provide a framework analysis of dual-hop hybrid Millimeter Wave Radio Frequency (RF)/Free Space Optical (FSO) MIMO relaying system. The source is equipped with multiple antennas and employs conjugate beamforming while the destination consists of multiple apertures with selection combining. The system also consists of a relay operating at amplify-and-forward mode. The RF channels are subject to Nakagami-m fading while the optical links experience the Málaga distribution. In addition, we introduce the impairments to the relay and receiver. In fact, the relay is impaired by the High Power Amplifier (HPA) nonlinearities while the receiver suffers from the In phase and Quadrature Imbalance. Moreover, we assume two types of HPA nonlinearities impairments called Soft Envelope Limiter (SEL) and Traveling Wave Tube Amplifier (TWTA). Closed-forms of the outage probability, the bit error probability, and the ergodic capacity are derived. Capitalizing on these performances, we derive the high SNR asymptotes to unpack insightful metrics such as the diversity gain. We also address the impacts of some key factors on the system performance such as the impairments, the interferers, the number of antennas and apertures and the pointing errors, etc. Finally, the analytical expressions are confirmed by Monte Carlo simulation.

In this work, we investigate the performance of a millimeter waves (mmWaves) cellular system with free space optical (FSO) backhauling. MmWave channels are subject to Nakagami-m fading while the optical links experience the Double Generalized Gamma including atmospheric turbulence, path loss and the misalignment between the transmitter and the receiver aperture (also known as the pointing errors). The FSO model also takes into account the receiver detection technique which could be either heterodyne or intensity modulation and direct detection (IM/DD). Each user equipment (UE) has to be associated to one serving base station (BS) based on the received signal strength (RSS) or Channel State Information (CSI). We assume partial relay selection (PRS) with CSI based on mmWaves channels to select the BS associated with the highest received CSI. Each serving BS decodes the received signal for denoising, converts it into modulated FSO signal, and then forwards it to the data center. Thereby, each BS can be viewed as a decode-and-forward (DF) relay. In practice, the relay hardware suffers from nonlinear high power amplification (HPA) impairments which, substantially degrade the system performance. In this work, we will discuss the impacts of three common HPA impairments named respectively, soft envelope limiter (SEL), traveling wave tube amplifier (TWTA), and solid state power amplifier (SSPA). Novel closed-forms and tight upper bounds of the outage probability, the probability of error, and the achievable rate are derived. Capitalizing on these performance, we derive the high SNR asymptotes to get engineering insights into the system gain such as the diversity order.

During a power system event, a system operator needs to conservatively reduce operating limits in real time as the changing system conditions are analyzed. The time it takes operators or their tools to develop new operating limits could affect millions of transmission system users, especially events classified as NERC Category D type events (extreme events resulting in the loss of two or more bulk electric system elements). Controls for the future evolution of the grid must be able to perform distributed real-time analysis, identify new reliability risks, and set new System Operating Limit's (SOLs) for real-time operations. In this paper we are developing requirements for distributed resilient agents that measure how systems able to operate at acceptable levels of normalcy despite disturbances or threats and define measures to determine how far the system is from boundary conditions and manage coordination between agent to achieve optimal global resiliency in the power system during the event.

As the complexity of the power grid increases, it becomes more susceptible to failures and cascading outages. Therefore, the resiliency of the power grid is severely jeopardized under fault conditions, unforeseen disturbances, and cyber or physical attacks. A common approach to alleviate vulnerabilities and further improve operational security is to recognize the critical lines or generators and adopt suitable remedial action schemes. In this paper, we use a power flow-based method to assess the vulnerability of the system before and after applying remedial action schemes. We focus on a modified version of the IEEE 9 bus system in Powerworld to examine our method. Our simulation results demonstrate the improvement in the system's resiliency.

This paper develops a multi-agent protection scheme for electric power distribution systems and microgrids with aggregated electronically coupled distributed energy resources (DER). The proposed protection scheme uses both voltage and current measurements to sense faults, and then trips only the faulted feeders, and broadcasts fault events to the main microgrid control system, and adjacent protective agents. The objective of this paper is to improve distribution system resilience by using a minimal communication protection scheme, and reducing power outages. Two study cases are presented. The EMTP-RV program is used to model the power system and the control systems of a PV based DER unit. The IEEE 34 bus test system is chosen for demonstration.

The electric power grid, as a critical national infrastructure, is under constant threat from cyber-attacks. State estimation (SE) is at the foundation of a series of critical control processes in a power transmission system. A false data injection (FDI) attack against SE can disrupt these control processes, crippling a power system and wreaking havoc in a region. With knowledge of the system topology, a cyber-attacker can formulate and execute stealthy FDI attacks that are very difficult to detect. Statistical and, more recently, machine learning approaches have been undertaken to detect FDI attacks on SE of the power grid. In this paper, we propose a Deep Learning (DL) based method to accurately detect stealthy FDI attacks on the SE of power grid. We compare the performance of the DL method with three popular machine learning algorithms, which are: gradient boosting machines (GBM), generalized linear modelings (GLM) and distributed random forests (DRF). All four algorithms analyze a dataset simulating the IEEE 14-bus system. The results demonstrate that these algorithms perform well in accurately and precisely detecting stealthy FDI attacks on the smart grid, with the DL-based approach showing best results.

Due to the characteristics and connectivity of today's Cyber-Physical Control Systems (CPCS) and critical infrastructures, cyber-attacks on these systems are currently difficult to prevent in an efficient and sustainable manner. Prevention and mitigation need accurate identification and evaluation of: system vulnerabilities, likely threats and attacks, and applicable hardening measures. Furthermore, the ability to prioritize hardening measures based on accurate assessments of threat risk and consequence and mitigation availability, applicability, and cost is also needed. To address this challenge we created HESTIA: High-level and Extensible System for Training and Infrastructure risk Assessment. In this paper, we describe the latest architecture and working principles of HESTIA. When fully developed, the HESTIA process and tool-set will enable CPCS engineers to, iteratively: 1) specify a CPCS, 2) select applicable attacks and hardening measures from a library, 3) check specifications for consistency and applicability, and 4) merge attack and hardening specifications into a new CPCS model. In addition, we add support for device specification templates. HESTIA enables the discovery of attack-defend scenarios through simulation and the design of optimal hardening strategies for a given CPCS. This paper is a shortened and updated version of a journal article entitled An architecture for HESTIA to appear in the International Journal of Internet of Things and Cyber-Assurance.

The development of superconducting systems for electric power is driven by the promise of improved efficiency, smaller size, and reduced weight as compared to existing technologies and by the possibility of new applications. Superconducting power components can also contribute to improved power quality and increased system reliability. This paper addresses historical developments and technology status of four superconducting power applications: cables, superconducting magnetic energy storage (SMES), fault-current limiters, and transformers. Today, SMES is the only fully functional superconducting system and it has seen only limited use at grid power levels. A few model or demonstration units exist for each of the other three applications. Superconductivity faces several hurdles on the path to widespread use. Perhaps the most important is the need for operating voltages of 100 kV or more. Though progress in this and other areas has been rapid, considerable development is needed before superconducting devices perform reliably in the utility environment. As a result, today, most initial installations are aimed at niche applications and will be installed where space is limited, where power demands are increasing over existing corridors, and/or where initial development costs can be offset by enhanced power grid performance.

While energy storage technologies do not represent energy sources, they provide valuable added benefits to improve stability power quality, and reliability of supply. Battery technologies have improved significantly in order to meet the challenges of practical electric vehicles and utility applications. Flywheel technologies are now used in advanced nonpolluting uninterruptible power supplies. Advanced capacitors are being considered as energy storage for power quality applications. Superconducting energy storage systems are still in their prototype stages but receiving attention for utility applications. The latest technology developments, some performance analysis, and cost considerations are addressed. This paper concentrates on the performance benefits of adding energy storage to power electronic compensators for utility applications.