Miracle-dz/UniFAR-FTUs huggingface dataset:
Rotordynamic Assessment for an Inside Out, High Speed Permanent Magnet Synchronous Motor

High speed and high rotor tip-speed, in particular, combined with high magnetic and electrical loading, are key enablers for obtaining high specific power in electric machines. The rotor described in this paper pushes the tip speed to about 80% of the speed of sound. An outer rotor design with a carbon-fiber retaining ring on the outer diameter (OD) was chosen to maintain high magnetic loading in the airgap while ensuring structural integrity at high speed. To achieve manufactural feasibility, a cantilevered rotor structure was proposed to suspend the rotor around the stator. This architecture introduces significant rotordynamic challenges, one of which is the ”trunnion effect,” a rotordynamic effect uncommon in traditional electric machines. This effect was identified when a discrepancy was observed during a rotor test and a root-cause analysis was performed to explain it. The original rotor dynamic model was modified to include this effect, and verified through a ping test. The trunnion effect, which significantly reduces the critical speeds, can be offset by selecting appropriate dimensions for the rotor end plate using the revised model. Thus, even in the presence of this effect, the proposed unconventional motor topology is confirmed to function reliably.
Modeling of Beam Electrothermal Actuators

Beam electrothermal actuators amplify the thermal expansion of pre-shaped beams and use the symmetrical structure to create a linear motion. These actuators, including V and Z shapes, are widely used in microsystems. Explicit analytical expressions are derived in this paper governing the structural deformation of these actuators due to electrothermal expansion and interaction with external lateral load. The analytical expressions are developed for an arbitrary initial shape of the actuator beams with symmetry and uniform cross-section. The modeling is based on the elastic beam theory, and all the modes of buckling are considered in the analytical solution. The solution and analytical expressions account for axial forces in tension and compression. The modeling considers the buckling with the third mode, which occurs at a certain limit of the axial compression and leads to significant variation in the stiffness of the actuator. This phenomenon is well studied for bistable pre-shaped beams, but related studies are limited for beam electrothermal actuators. As a case study, the V shape actuator is specifically investigated. The modeling shows very good agreement with finite element simulations and experimental data based on micro-machined in-plane silicon actuators. [2020-0262]
What Do Pedestrians See?: Visualizing Pedestrian-View Intersection Classification

Extensive research has been carried out on intersection classification to assist the navigation in autonomous maneuvering of aerial, road, and cave mining vehicles. In contrast, our work tackles intersection classification at pedestrian-view level to support navigation of the slower and smaller robots for which it is too dangerous to steer on a normal road along with the usual vehicles. Particularly, we focus on investigating the kind of features a network may exploit in order to classify intersection at pedestrian-view. To this end, two sets of experiments have been conducted using an ImageNet-pretrained ResNet-18 architecture fine-tuned on our image-level pedestrian-view intersection classification dataset. First, ablation study is performed on layer depth to evaluate the importance of high-level feature, which demonstrated superiority in using all of the layers by yielding 77.56% accuracy. Second, to further clarify the need of such high level features, Class Activation Map (CAM) is applied to visualize the parts of an image that affect the most on a given prediction. The visualization justifies the high accuracy of an all-layers network.
Electromechanical Dynamics Analysis of Pole-Piece Rotors in Pseudo Direct-Drive Wind Turbine Generators

This paper analyses the electromechanical dynamics of the pole-piece rotors in a pseudo direct-drive wind turbine generator. The investigated generator has a rated power of 10 MW and was designed in the INNWIND.EU project. One way coupled finite element analysis (FEA) was used to calculate the rotor dynamic defections caused by electromagnetic forces in the air gap. Results show that the deflection exceeds the air gap length which is not mechanically feasible. To solve the problem, three structural modifications are proposed and tested in FEA to reduce the pole piece deflection significantly. The results of the three solutions are compared to idenfity the most promising one. It shows that a ribbed rotor piece topology is the most suitable option because it achieves a reasonable tradeoff between the torque generation and mechanical deflection.
A Current-Attenuator for Performing Read Operation in Memristor-Based Spiking Neural Networks

This paper presents a current attenuator fabricated in a CMOS 180nm technology, which works based on a CMOS ladder scheme. The attenuation factor is 104.14 dB, while it shows a non-linearity feature of less than 1.8 %. The circuit occupies an area of 2448 µm2. Since the output current could be as low as tens of femtoamperes, an on-chip testing circuit is also proposed to make the lab-measurements as accurate as possible. The final results show that chip-measurements are following simulations. As a demonstrator, the current attenuator is internally connected to a compact CMOS neuron cell. The output membrane potential shows that the neuron is generating a real-time firing modality, and consequently approves that the current-attenuator is working robustly.
Basic steps for building and using a functional near infra-red spectroscopy (fNIRS) System

Brain-computer interface (BCI) has been in the center of interest for many researchers for the past few decades, resulting in various methods to obtain signals from the brain and algorithms to process the signal. Among those brain signal obtaining methods under research, functional near infra-red spectroscopy (fNIRS) is a method with great potential of acquiring accurate data of neural activities. This paper provides the fundamentals for building an fNIRS system and how to process the acquired data to obtain a signal relevant of neural activity. Customization for particular applications is possible enabling novice brain researchers to join the research field and further improve BCI.
Adding Terrain Height to Improve Model Learning for Path Tracking on Uneven Terrain by a Four Wheel Robot

Closely tracking a defined path by a wheeled mobile robot on a three-dimensional surface is important for accurate movement on uneven terrain. Conventional methods in two dimensions are difficult to extend to three dimensions due to the computational complexity in finding wheel-terrain interactions. Learning based methods bypass the need for explicit modelling and can accurately predict these dynamic relations. We use learning based Model Predictive Controller (MPC) for path tracking by a four-wheel robot. A neural network is used as a model due to its capability for learning complex state transition dynamics. Learning terrain height information aids the MPC on uneven terrain. The algorithm is rigorously tested in simulation on a variety of terrain profiles to track paths by a four wheel robot's center of mass. Results show the method is robust to model errors and that our novel method of incorporating terrain height information significantly improves performance on terrains with high frequency surface profile changes.
T-A Formulation for the Design and AC Loss Calculation of a Superconducting Generator for a 10 MW Wind Turbine

The current capacity of high-temperature superconductors (HTS) has encouraged several applications of these materials in electric power systems. These applications in electrical machines represent a promising solution for more compact and efficient designs. Despite no measurable resistance in the superconducting state, HTS could experience losses under time changing transport current or magnetic field. Therefore, loss estimation is a key input for the design. Maxwell’s equations in the T-A formulation form can be used to model and estimate losses in the superconducting tapes of an electrical machine. This formulation requires the current as a function of time in each superconducting tape as an input. A methodology to calculate this current distribution is presented in this article. The procedure introduces a previous step in the building model process and allows a better connection of the machine design with the estimation of losses in the superconductor in order to get a more efficient machine. The approach is applied to a 10 MW superconducting generator, where over one thousand tapes cross-sections are modelled in 2D. The superconductor’s non-linear behaviour and critical current density anisotropy are considered. Losses are estimated for different designs and a sensitivity analysis is presented for different temperatures and frequencies, in addition to other alternatives to reduce losses.
LQR-based affine formation control for multi-agent systems

Affine formation control has been proved to be an effective tool in altering formation shapes for multiple robots to adapt to the change of working space. This paper studies the problem of optimal affine formation control based on LQR performance index. By taking both the internal potential and the control efforts of all agents into consideration, the control gain is uniquely determined under which the cost function is minimized. It is shown that the control gain is dependent on the agents' initial states as well as their connection relationship. Numerical simulations are presented to validate the theoretical results.
Closed-loop Solution to Optimal Control for Discrete-Time Systems with Final State Constraints

This paper is concerned with the linear quadratic (LQ) control problem of discrete-time systems with terminal state constraints. Firstly, lagrange multiplier is used to convert the final constraints into parts of cost function. Secondly, on the basis of the maximum principle, the solvability condition is presented to guarantee the existence of the optimum solution and then the corresponding optimal feedback controller is designed. An illustrate example is provided to demonstrate the effectiveness of the methods proposed in this paper.
Trajectory design of an Aircraft for Circular Motion

In this paper we propose an autopilot control strategy for a small radio controlled aircraft aiming to follow a circular path with a desired radius. In contrast to the usual way to compute the error as the distance between the plane current space position and the desired flight trajectory path (for example a circle of radius r0), here we propose an alternative way to compute the scalar quantity E(t)) such that the aircraft moves in a spiral path of a decreasing/increasing with time radius to approach the circle with desired radius r0. Our particular choice of error term is intended to cause only gradual changes in the aircraft’s direction so as to prevent unstable flight due to over-control.
Development of Haptic Bracelets Based Arm Swing Feedback System for Stroke Survivors

For stroke survivors, the ultimate goal of rehabilitation training for community life is to increase the dynamic stability, which can be helped by increasing the walking speed or symmetry. Several researches have reported the use of haptic stimulation to increase the dynamic stability of gait. Haptic systems have many advantages such as, portability and low-cost, that make them extremely suited for rehabilitation applications. However, until now the use of these systems has been focused mainly on the lower limbs. Gait is a harmonic motion that includes both the upper and lower limbs. A study with people suffering from Parkinson’s Disease showed that it is possible to bring about spatiotemporal gait changes using an arm swing cueing device. Therefore, in this paper, we present the development and verification of a haptic bracelet designed to deliver arm swing based haptic feedback for the rehabilitation of stroke survivors. The presented system is portable, composed of inexpensive sensors and it can measure the arm swing angle correctly regardless of the location or direction of the sensor. The measurements made using the developed system were compared to those made using a standard motion tracking system and only an acceptable amount of error was found. The developed system may be used to characterize the effect of upper extremity motion modification during gait. It may also be used as a system for improving gait speed and symmetry of stroke patients using haptic vibration feedback.
Robotic Tidy-up Tasks using Point Cloud-based Pose Estimation

To perform a tidy-up task using a robot arm, it is necessary to estimate the pose of various objects. Generally, pose estimation requires the CAD model of an object, but these models of most objects in daily life are not available. Therefore, this study proposes an algorithm to estimate the pose of unknown objects without the help of CAD models. Furthermore, the strategies on grasping and object manipulation for robotic tidy-up are also proposed. First, the geometric and color information are considered together to segment the various objects in the aligned point cloud. Then, the principal component analysis (PCA) scheme is used to estimate the object frame and the placement state. Based on this estimation, the proposed strategies were introduced to make it possible to tidy up the objects. It was shown from various experiments that the proposed method can be effectively applied to the robotic tidy-up tasks.
Delay dependent stability of singular T-S fuzzy systems with additive time varying delays

This work considers the problem of delay dependent stability analysis for singular Takagi-Sugeno systems with additive time varying delays. The proposed method is based on the use of the generalized free-matrix based Bessel-Legendre integral inequality. The result is a new stability condition in terms of Linear Matrix Inequality (LMIs). The simulation results show the effectiveness of the proposed technique.
Evaluation of Three Cooling Concepts for an Electric Vehicle Motor – Lumped Parameter Models

Three different cooling solutions for the same permanent magnet electric vehicle traction machine are compared using 2D finite element method generated loss maps and a thermal lumped parameter network. Two water jackets, with a wave and a spiral shaped channel, are compared to an end-shield cooling channel with end winding potting. The coolant convection is estimated using 3D conjugate heat transfer simulation software, presented in an accompanying paper. The continuous and overload torque capability are determined as well as the winding temperatures and energy losses during a set of low, middle and high-speed drive cycles. The results indicate very similar performance for the two water jackets. With the end-shield cooling the continuous torque is considerably higher at low speed levels, higher torque levels can be sustained for a certain time, and the drive cycle winding temperatures and losses are lower compared to the cooling jackets.
Output-Capacitance Hysteresis Losses of Field-Effect Transistors

Resonant-type power converters are supposed to generate zero switching losses during soft-switching operation. In recent research, unexpected switching losses were reported in these converters, which were attributed to a large-signal hysteresis observed in the output-charge versus voltage (QV) characteristics of the power device. Since these converters subject the power semiconductor switch to different levels of peak voltages based on design requirements, the dependence of hysteresis losses on the voltage range is important. In this work, planar-Si, Si super-junction, SiC and GaN power device structures are investigated, and categorized based on their QV patterns. We report that for different device technologies, the large-signal hysteresis patterns of output charge show diverse dependencies on the excitation voltage amplitude. The frequency dependence of the hysteresis losses is also analysed and discussed. The presented results provide important insights in identifying the root causes for output-charge hysteresis, and may help to improve device spice models to properly account for soft-switching losses.
Calibration-Free Calorimeter for Sensitive Loss Measurements: Case of High-Frequency Inductors

Wide-band-gap technologies enable ultra-high efficiencies in high-frequency power conversion. However, inadequate accuracies in electrical measurements could lead to spurious efficiency measurements, even above 100%. Furthermore, bandwidth limitations, particularly for current probing, delay mismatches between current and voltage probes, loading effects and electromagnetic interferences make electrical techniques inappropriate for measuring extremely-low losses in switches with high dv/dt and di/dt values and magnetic components with high-frequency excitations. Calorimetric methods overcome this issue by a direct loss measurement through the generated heat. Nevertheless, limited ranges and accuracies of existing systems hinder their application in sensitive measurements. Moreover, time-consuming calibrations with extensive data processing impede rapid design assessments. In this work, we further investigate a previously proposed closed-type double-chamber calorimeter and present its high accuracy for the evaluation of low levels of losses in high-frequency power inductors. The system provides adjustable cooling and can measure losses as low as 500 mW, enabling evaluation of high-performance power converters and their components with no dependencies on the geometries of the evaluated devices/systems.
Analysis and Evaluation of Sound-based Positioning Techniques for Short Distances

Sound-based positioning systems have shown a great potential in underwater and indoor applications. These systems are been used for robot tracking and navigation due to their simplicity and low cost. In fact, sound-based location techniques usually present acceptable positioning precision in obstacle-free wide areas due to the long wavelengths of sound signals. However, short-distance positioning is also useful for robot tracking and navigation, specially in the field o f m icro robotics. Nevertheless, sound-based positioning is not commonly applied in small areas because of the short propagation times. Hence, this work analyzes and evaluates experimentally typical trilateration techniques used for the positioning of targets through acoustic signals and low-cost hardware in distance-restricted environments. The long-term goal of this work is to make use of sound-based positioning techniques in micro robots for their tracking and navigation in small-scale areas. Obtained results show that the technique known as TDoA (time-difference of arrival) presents a good precision, generating errors as low as 1 cm in a 50×50 cm area.
MARLA-SG: Multi-Agent Reinforcement Learning Algorithm for Efficient Demand Response in Smart Grid

The population is sharply growing in the last decade, resulting in non-potential power requests in dense urban areas, especially with the traditional power grid where the system is not compatible with the infrequent changes. Smart grids have shown strong potential to effectively mitigate and smooth power consumption curves to avoid shortages by adjusting and forecasting the cost function in real-time in response to consumption fluctuations to achieve the desired objectives. The main challenge for the smart grid designers is to reduce the cost and Peak to Average Ratio (PAR) while maintaining the desired satisfaction level. This article presents the development and evaluation of a Multi-Agent Reinforcement Learning Algorithm for efficient demand response in Smart Grid (MARLA-SG). Also, it shows a simple and flexible way of choosing state elements to reduce the possible number of states, regardless of the device type, range of operation, and maximum allowable delay. It also produces a simple way to represent the reward function regardless of the used cost function. SARSA (State-Action-Reward-State-Action) and Q-learning schemes are used and attained PAR reduction of 9.6%, 12.16%, and an average cost reduction of 10.2%, 7.8%, respectively.
Finite-Time Time-Varying Group Formation Tracking for High-Order Multi-Agent Systems with Mismatched Disturbances under Directed Graphs

Finite-time time-varying group formation (FT-TVGF) tracking control problems for high-order multi-agent systems (MASs) are studied in this paper. Different from previous work, the approaches proposed in this paper combine group formation tracking control with finite-time control, not only that, the agents in each group can achieve time-varying sub-formations and the relative configuration between different groups can be adjusted simultaneously. First, all agents are divided into three types, including the virtual leader, the group leader, and the follower. The virtual leader is added to plan the trajectory of MASs. Subgroups can be interacted with each other by the communication among group leaders. Followers achieve the finite-time formation tracking of group leaders. Then the disturbance observer is constructed to estimate the mismatched disturbances of all group leaders and followers in finite time. Furthermore, based on finite time control theory and observer theory, a distributed control protocol is presented to make MASs realize FT-TVGF tracking under directed graph. The proof of close-loop stability of MASs is accomplished using Lyapunov theory. Finally, numerical simulations verify the theoretical analysis of this paper.
Active-Flux-Based Sensorless Control for Permanent Magnet Synchronous Motor by Variable-Gain Sliding-Mode Observer

This paper presents a variable-gain sliding-mode observer (VGSMO) based on active flux to achieve sensorless control for interior permanent magnet synchronous motor (IPMSM). A model of PMSM with the "active flux" concept is first described. Then, a sensorless control method is presented based on VGSMO and Fractional-Order Phase-Locked Loop (FO-PLL). The VGSMO is designed to estimate the active flux, and the FO-PLL is designed to estimate the rotor speed and position precisely. In particular, the variable of gain matrixes of VGSMO eliminates the chattering of sliding-mode successfully. The stability analysis of VGSMO is also given in detail. Finally, the results of the simulations are given to demonstrate the accuracy, validity of the proposed method.
Predictive Maintenance for SME in Industry 4.0

Technology and businesses go hand in hand in this modern bustling work environment. The rapid change in the IT sector necessitates that corporations change accordingly. Industry 4.0 carries a plethora of vital, innovative systems that could optimise products and make services more efficient. Predictive Maintenance is one such instance where IIoT improves various industrial processes and the products generated using these processes. Therefore, this paper aims to present a literature review about the recent technologies available in predictive maintenance with Industry 4.0. The survey focuses on the technologies adopted by all kinds of industries, however, a special emphasis has been awarded to Small and Medium Enterprises. It has been organised based on industrial goals, architecture, and methodology which can help the stackholders to take informed decision for their business. This work aims to summarize the recent advancements in the IIoT with a corporative point-of-view.