During the past decade, the model predictive control (MPC) of power electronics and drives has witnessed significant advancements in both dynamic performance and range of applications. However, researchers still encounter challenges with the optimal design of weighting factors, and this lowers the capabilities derivable from MPC. This study first reviews the different weighting factor design techniques proposed in the literature for power electronics and electrical drives (applied to wind/solar energy conversion, microgrids, grid-connected converters and other high performance converter-based systems). They are grouped under heuristic, offline tuning, sequential, and online optimization methods. Next, the study provides real-time hardware-in-the-loop comparative results for the implementation of four weighting factor design techniques on a grid-connected two-level back-to-back power converter-based permanent magnet synchronous generator wind turbine system. Through these laboratory results, the advantages and limitations of the different weighting factor design methods are highlighted.

A not yet available look-up table (LUT) based optimal feedforward torque control (OFTC) method for squirrel- cage induction machines (SCIMs) is presented. It is based on: (i) a generic transformer-like machine model in an arbitrarily rotating (d,q)-reference frame, considering nonlinear flux linkages and iron losses in the stator laminations; (ii) machine identification by evaluating steady-state measurements over a grid of (d,q) stator currents, producing frequency-dependent machine maps for e.g. flux linkages, torque, iron resistance and efficiency; and (iii) numerical optimization and extraction of OFTC look- up tables for optimal stator current references depending on reference torque and electrical frequency. In order to increase reproducibility, a feedback temperature controller is employed to keep the stator winding temperature constant. Moreover, throughout the identification, the electrical frequency is kept con- stant (per data set) by adapting the machine speed accordingly using a speed-controlled prime mover; this way the impact of iron losses becomes more balanced than for constant speed operation. The presented measurement results confirm that compared to constant flux operation or scalar V/Hz control, efficiency can be increased particularly in part-load operation by up to 7 %.

New analytical expressions and numerical results for the quality factor and directivity as well as computationally convenient expressions for the input admittance of a symmetrical biconical antenna of arbitrary length $L$ and cone angle $\theta_0$ are presented. The quality factor for a wide-angle biconical antenna is shown to very closely approach the Chu’s limit of $Q = (kL)^{-1}\{1+(kL)^{-2}\}$. Numerical calculations based on the analytical formula for antenna admittance confirm the conjecture that Foster’s reactance theorem remains invalid even for perfectly conducting antennas. Furthermore, the variation of directivity of a wide-angle biconical antenna is a slowly varying function of its electrical length and is shown to depart significantly from that of a thin cylindrical dipole.

In this paper, we propose the concept of Android Printing, which is printing a full android, including skin and mechanical components in a single run using a multi-material 3-D printer. Printing an android all at once both reduces assembly time and enables intricate designs with a high degrees of freedom. To prove this concept, we tested by actual printing an android. First, we printed the skin with multiple annular ridges to test skin deformation. By pulling the skin, we show that the state of deformation of the skin can be adjusted depending on the ridge structure. This result is essential in designing humanlike skin deformations. After that, we designed and fabricated a 3-D printed android head with 31 degrees of freedom. The skin and linkage mechanism were printed together before connecting them to a unit combining several electric motors. To confirm our concept's feasibility, we created several motions with the android based on human facial movement data. In the future, android printing might enable people to use an android as their own avatar.

The present study deals with the fabrication of light-reflecting materials used in pixelated scintillator detectors. For the first time, the reflecting surfaces for pixels of different sizes (from 0.8 to 3.2 mm) were obtained via a low-cost DLP 3D printing technique. The material for the reflectors was the new composite of transparent ultraviolet light-cured resin and TiO2 as a light-scattering filler. It was observed that TiO2 showed better performance compare to other pigments such as BaSO4, hBN or cubic zirconia. The object formation rate was about 1 cm per hour with the possibility to produce several parts simultaneously that simplifies the wrapping procedure. It was found that the regular grooves pattern of the fabricated parts (staircase effect) could increase a light collection from a scintillator. The reflective properties of such surfaces were comparable to conventional reflection coating (e.g., Teflon wrapping). Presented at the 2019 IEEE NSS & MIC conference, Manchester, UK. 14 pages, 12 figures, 1 table. Journal reference: Optical Materials V. 108, October 2020, p. 110393.

The automated analysis of digital human communication data often focuses on specific aspects like content or network structure in isolation, while classical communication research stresses the importance of a holistic analysis approach. This work aims to formalize digital communication analysis and investigate how classical results can be leveraged as part of visually interactive systems, which offers new analysis opportunities to allow for less biased, skewed, or incomplete results. For this, we construct a conceptual framework and design space based on the existing research landscape, technical considerations, and communication research that describes the properties, capabilities, and composition of such systems through 30 criteria in four analysis dimensions. We make the case how visual analytics principles are uniquely suited for a more holistic approach by tackling the automation complexity and leverage domain knowledge, paving the way to generate design guidelines for building such approaches. Our framework provides a common language and description of communication analysis systems to support existing research, highlights relevant design areas while promoting and supporting the mutual exchange between researchers. Additionally, our framework identifies existing gaps and highlights opportunities in research areas that are worth investigating further. With this contribution, we pave the path for the formalization of digital communication analysis through visual analytics.

We present a method to super-resolve voxelized point clouds down-sampled by a fractional factor, using look-up-tables (LUT) constructed from self-similarities from its own down-sampled neighborhoods. Given a down-sampled point cloud geometry Vd, and its corresponding fractional down-sampling factor s, the proposed method determines the set of positions that may have generated Vd, and estimates which of these positions were indeed occupied (super-resolution). Assuming that the geometry of a point cloud is approximately self-similar at different scales, LUTs relating down-sampled neighborhood configurations with children occupancy configurations can be estimated by further down-sampling the input point cloud to Vd2 , and by taking into account the irregular children distribution derived from fractional down-sampling. For completeness, we also interpolate texture by averaging colors from adjacent neighbors. We present extensive test results over different point clouds, showing the effectiveness of the proposed method against baseline methods.

We propose an embedded attribute encoding method for point clouds based on set partitioning in hierarchical trees (SPIHT) [1]. The encoder is used with the region-adaptive hierarchical transform [2] which has been a popular transform for point cloud coding, even included in the standard geometry-based point cloud coder (G-PCC) [3],[4]. The result is an encoder that is efficient, scalable, and embedded. That is, higher compression is achieved by trimming the full bit-stream. G-PCC’s RAHT coefficient prediction prevents the straightforward incorporation of SPIHT into G-PCC. However, our results over other RAHT based coders are promising, improving over the original, nonpredictive RAHT encoder, while providing the key functionality of being embedded.

Nowadays, Solar power is utilized more in domestic, commercial, and industrial applications. Solar energy is renewable energy which is produced from sun heat. In 2020 India solar installed capacity was 34,627 MW. In this paper developed an experimental setup for solar panel power measurement. In this current, voltage and light intensity has been measured. Declination angle of sun to earth is +23.5°degrees, -23.5°degrees. The model of sun is represented by an incandescent bulb light and the angles set up manually. In this explained about solar power output at load side and see the variation between power and load resistance. Solar panel is generated power by light intensity applied by using incandescent light bulb. The light intensity changed by using a voltage regulator. The power is measured by using voltmeter and ammeter readings. Solar energy is to emulate the solar panel output power characteristics. The model of sun was taken as an incandescent bulb light and placed on the circular iron track to change east to the west. By changing the position of the bulb and changing the bulb light intensity with the help of the D.C speed regulator. Solar panel is placed in such a way that it freely moves to certain angles. By taking voltmeter and ammeter readings calculate the power. The graph is drawn between resistance versus power, the unique source of energy. The main aim of the paper is. Ensure that the maximum power output occurs at load which is taken as a resistor bank.

Fault diagnostic methods with fuzzy logic methods, SVM, KNN and artificial intelligence systems have been used in complex systems such as wind turbines, gas turbines, power distribution systems, power transformers and rotary machines, but in the specific field of distributed control systems, the vacancy of this topic is strongly felt. Due to the need of the industry to detect faults quickly and in a timely manner in all modes of sensors, actuators, outputs and control logics to maintain expensive, valuable resources, important and complex equipment, it is very necessary to enter this topic. In this paper, a suitable theoretical and practical basis for diagnosing various types of faults in the DCS of a gas refinery is done. The fact that the operator quickly identifies the area and the cause of the fault can avoid huge losses in terms of downtime. Automation of fault diagnosis in DCS has not been explicitly mentioned in any article or book, and here the plan is presented for the first time. In this design, we connect MATLAB classification apps to the industrial system like DCS, then data are analyzed by SVM and KNN methods to detect faults. The results show that faults can be detected with a probability of more than 85% accuracy without the need for on-site expert force and with much less time.

Continuous verification of network security compliance is an accepted need. Especially, the analysis of stateful packet filters plays a central role for network security in practice. But the few existing tools which support the analysis of stateful packet filters are based on general applicable formal methods like Satifiability Modulo Theories (SMT) or theorem prover and show runtimes in the order of minutes to hours making them unsuitable for continuous compliance verification. In this work, we address these challenges and present the concept of state shell interweaving to transform a stateful firewall rule set into a stateless rule set. This allows us to reuse any fast domain specific engine from the field of data plane verification tools leveraging smart, very fast, and domain specialized data structures and algorithms including Header Space Analysis (HSA). First, we introduce the formal language FPL that enables a high-level human-understandable specification of the desired state of network security. Second, we demonstrate the instantiation of a compliance process using a verification framework that analyzes the configuration of complex networks and devices - including stateful firewalls - for compliance with FPL policies. Our evaluation results show the scalability of the presented approach for the well known Internet2 and Stanford benchmarks as well as for large firewall rule sets where it outscales state-of-the-art tools by a factor of over 41.

The paper presents three new 26-connected constant feedrate incremental step algorithms that can be used in practical situations in CNC machining tools. The 1st, the perfect 3D line IPO is 100% incremental, the word “perfect” means that the accuracy can be much better than the accuracy of Bresenham’s 3D line (e.g. accuracy can be 37% worse). The simplified state diagram computes one perfect major axis points and possibly a perfect non-major axis point. The selection criterion uses the real 3D distance to the line. The 2nd, the perfect 3D curve IPO is a QSIC-algorithm (intersection of two quadrics). The selection criterion uses the “Relative Curve Measurement Theorem” extended to quadrics and QSICs. The consequences of this theorem are crucial, it means that one must not calculate the time-consuming distance to the 3D curve, but it suffices to calculate the RMDPL or the relative minimal distance of two candidate points to the polar line of the QSIC with respect to the midpoint of the candidate points. As the midpoints are close to the curve, the polar lines enclose and inclose the curve. Theoretical, the RMDPL is fundamental, it is the core of all the successful 2D incremental step algorithms and the paper proves that it is the core of the 3D incremental step algorithms or the 3D reference pulse IPOs. Thanks to the RMDPL, the paper represents QSICs in a unique way comparable with 3D-lines. The 3rd, Bresenham’s imperfect 3D curve IPO is less accurate but super-fast and can be used in many practical situations as the maximum error (MaxErr) is bounded to 0.707. The curve algorithms can have singular points, but that problem is simple solved. Each curve is a sub-segment of a monotonic curve from the starting extreme point to the ending extreme point. All the extreme points and the singular points are offline precomputed as the intersection points of three quadrics. The constant feedrate of sampled-data curves is clear when the arc length is known, but the real time calculation of the arc length of incremental step curves was until now an open problem. The former paper used the super-fast PRM-cs algorithm for 3D-lines and 2D curves and the same constant feedrate algorithm (actually, a real time length algorithm) can be used even in integer form. The implementation of the constant feedrate algorithm to a 26-connected curve with high accuracy turns out to be piece of cake in contrast to the sampled-data curves. All IPOs can be converted to constant feedrate listSIM-IPOs which can be used in real time in rigid simplified CNC machine tools.

Unmanned aerial vehicles (UAVs) and Terahertz (THz) technology are envisioned to play paramount roles in next-generation wireless communications. In this paper, we present a novel secure UAV-assisted mobile relaying system operating at THz bands for data acquisition from multiple ground user equipments (UEs) towards a destination. We assume that the UAV-mounted relay may act, besides providing relaying services, as a potential eavesdropper called the untrusted UAV-relay (UUR). To safeguard end-to-end communications, we present a secure two-phase transmission strategy with cooperative jamming. Then, we devise an optimization framework in terms of a new measure − secrecy energy efficiency (SEE), defined as the ratio of achievable average secrecy rate to average system power consumption, which enables us to obtain the best possible security level while taking UUR’s inherent flight power limitation into account. For the sake of quality of service fairness amongst all the UEs, we aim to maximize the minimum SEE (MSEE) performance via the joint design of key system parameters, including UUR’s trajectory and velocity, communication scheduling, and network power allocation. Since the formulated problem is a mixed-integer nonconvex optimization and computationally intractable, we decouple it into four subproblems and propose alternative algorithms to solve it efficiently via greedy/sequential block successive convex approximation and non-linear fractional programming techniques. Numerical results demonstrate significant MSEE performance improvement of our designs compared to other known benchmarks.

Owing to the mobility of a wearable antenna and the unpredictable body-centric communications environment, dual-polarization antennas are essential for both communications and energy harvesting. This paper presents a dual-polarized four-port textile antenna/rectenna for wearable simultaneous wireless information and power transfer (SWIPT) applications. The proposed antenna utilizes dual ports for both off-body communication and energy harvesting from horizontal and vertical polarizations. The antenna maintains a 100 MHz bandwidth with an S11 under -10 dB around 2.4 GHz in the presence and absence of the human body, and at least 10~dB small-signal and large-signal isolation between all ports. The antenna maintains a 70-88% measured total efficiency and 8.4–9.6 dBi gain for various on-phantom positions across both communication ports. The measured mutual coupling is under -10 dB between co-polarized rectenna/antenna ports, and under -16~dB between orthogonally-polarized ports. A high RF to DC peak power conversion efficiency of over 70% (+-5%) is achieved with a broadside harvesting pattern. Based on the proposed antenna’s performance, SWIPT microstrip antennas can be adopted for both full-duplex and MIMO applications, significantly reducing the complexity of future battery-free networks for both wearable and non-wearable applications.

Measurement of human body movement is an essential step in biomechanical analysis. The current standard for human motion capture systems uses infrared cameras to track reflective markers placed on the subject. While these systems can accurately track joint kinematics, the analyses are spatially limited to the lab environment. Though Inertial Measurement Unit (IMU) can eliminate the spatial limitations of the motion capture system, those systems are impractical for use in daily living due to the need for many sensors, typically one per body segment. Due to the need for practical and accurate estimation of joint kinematics, this study implements a reduced number of IMU sensors and employs machine learning algorithm to map sensor data to joint angles. Our developed algorithm estimates hip, knee, and ankle angles in the sagittal plane using two shoe-mounted IMU sensors in different practical walking conditions: treadmill, level overground, stair, and slope conditions. Specifically, we proposed five deep learning networks that use combinations of Convolutional Neural Networks (CNN) and Gated Recurrent Unit (GRU) based Recurrent Neural Networks (RNN) as base learners for our framework. Using those five baseline models, we proposed a novel framework, DeepBBWAE-Net, that implements ensemble techniques such as bagging, boosting, and weighted averaging to improve kinematic predictions. DeepBBWAE-Net predicts joint kinematics for the three joint angles under all the walking conditions with a Root Mean Square Error (RMSE) 6.93-29.0% lower than base models individually. This is the first study that uses a reduced number of IMU sensors to estimate kinematics in multiple walking environments.

A new Modular Multilevel Converter with Interleaved half-bridge Sub-Modules (ISM-MMC) is proposed in this paper. The ISM-MMC exhibits a higher modularity and scalability in terms of current ratings with respect to a conventional MMC, while preserves the typical voltage level adaptiveness. The ISM-MMC brings the known advantages of classical MMC to low-voltage, high-current applications making it a novel candidate for the sector of ultra-fast chargers for all types of electrical vehicles (EV). This advanced topology makes it possible to easily reach charging power of the EV charging system up to 4.5 MW and beyond with low-voltage supply. To operate the new converter, a hybrid modulation scheme that helps to exploit advantages of the interleaving scheme, is implemented, and explained in this paper. It has been verified that the typical MMC control methods are still applicable for ISM-MMC. A comparative study between classical MMC and ISM-MMC configurations in terms of output characteristics and efficiency is also given. Furthermore, it has been demonstrated that the number of ac voltage levels is synthetically multiplied by the number of interleaved half- bridge legs in submodules. Simulations, Hardware-in-the-Loop and Experimental tests are carried out to demonstrate the feasibility of the proposed topology and implemented modulation scheme.

Modular multilevel power electronic converters are considered an increasingly critical family of converters for myriad high voltage high power applications. With the ever-growing emphasis on electrification of the economy, they play a crucial role in serving energy sources and loads whose electrical ratings go beyond the ratings of the conventional power electronic building blocks. In particular, modular multilevel converter (MMC) topology enjoy its dominance in such applications due to modularity, scalability, performance and fault-tolerance capability. However, the MMC topology design imposes low-frequency ac components on the module capacitors and thus is inhibited by the capacitor size. Capacitor sizing plays a significant role in the overall system’s size, cost and reliability. This paper introduces a minimal capacitor module based topology for DC to three-phase AC conversion. The unique design feature of the module includes minimal capacitor requirement due to elimination of single-phase ac power processing requirements. Together with improved power density, reduction of capacitor size permits the use of only film capacitors thus eliminating the weakest link of the overall system. Along with the step-by-step analytical derivation of the proposed approach, the paper presents detailed simulation studies, comparative analysis and experimental results from a proof-of-concept laboratory-scale prototype.

Detection for high-dimensional multiple-input multiple-output (MIMO) and massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), for both single-user (SU) and multi-user (MU) scenarios. The complexity of SD is mainly determined by the initial radius (IR) method and the number of visited nodes during detection. This paper employs an efficient IR and proposes a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, an introduced hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented. The trade-offs are achieved by either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless of the level of noise. The decoding gain of SD compared to the low-complexity linear detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware implementation aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.