Switch Matrix Research Articles

Followed The Regularized Leader (FTRL) prediction model based photovoltaic array reconfiguration for mitigation of mismatch losses in partial shading condition

Non-uniform irradiance, for example, partial shading, would affect the performance of the whole Photovoltaic (PV) array and reduce the output power. Since the layout of PV array is also an important factor influencing the performance of PV array, reconfiguration scheme has been researched popularly. Since plenty of array reconfiguration techniques are not realistic to be implemented in reality, in this paper considering the simplicity, robustness and economical aspects, a Followed The Regularized Leader algorithm (FTRL) regression prediction model based switches controlled PV array reconfiguration method is proposed to enhance the power output from solar PV array and alleviate the effects of partial shadings. The proposed scheme has no additional labor and wire requirement, since the proposed connection architecture of PV array involves no complex switch matrix design. Subsequently, to testify the performance of the proposed scheme, simulations with various shades in different PV arrays are made and evaluation parameters, for example, Fill Factor (FF) and mismatch loss are calculated. Furthermore, outdoor experiments are conducted to validate the simulation and the analyses. Besides, extensive analyses of cost analysis and energy savings are given. At last, a comprehensive evaluation is performed to check the quality of the proposed scheme by comparing with various techniques in literature.

Semantic Coding and Model Reconstruction of Multifunction Radar Pulse Train

Retrieving the working modes of multifunction radar from electronic reconnaissance data is a difficult problem, and it has attracted widespread attention in the field of electronic reconnaissance. It is also an important task when extracting benefits from big electromagnetic data and provides straightforward support to applications, such as radar type recognition, working state recognition, radar intention inferring, and precise electronic jamming. Based on the assumption of model simplicity, this study defines a complexity measurement rule for multifunction radar pulse trains and introduces the semantic coding theory to analyze the temporal structure of multifunction radar pulse trains. The model complexity minimization criterion guides the semantic coding procedure to extract radar pulse groups corresponding to different radar functions from pulse trains. Furthermore, based on the coded sequence of the pulse train, the switching matrix between different pulse groups is estimated, and the hierarchical working model of multifunction radars is ultimately reconstructed. Simulations are conducted to verify the feasibility and performance of the new method. Simulation results indicate that the coding theory is successfully used in the proposed method to automatically extract pulse groups and rebuild operating models based on multifunction radar pulse trains. Moreover, the method is robust to data noises, such as missing pulses.

Ultralow-VπL Silicon Electro-Optic Directional Coupler Switch With a Liquid Crystal Cladding

An ultralow-V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">π</sub> L photonic switch device is demonstrated utilizing the high optical and electrical field confinement in silicon slot waveguides coupled with the strong electro-optic response of nematic liquid crystals. A silicon photonic directional coupler switch with a modulation efficiency of 0.0195 V·mm and a loss-efficiency product of 0.0624 V·dB is achieved. The 1.5 mm long device is based on two-mode interference within a single slot waveguide resulting in a V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">π</sub> of 0.013 V and an extinction ratio of ~ 9dB at 1550 nm wavelength. The power consumption of the photonic switch is estimated to be below 0.6 nW and it possesses a response time of <; 1.5 ms. A comparative performance study between the directional coupler switch and a Mach-Zehnder Interferometer (MZI) switch is performed. The directional coupler switch is projected to have a smaller footprint and lower optical loss compared to a similar design MZI switch making it a strong candidate for switch matrix designs and applications.

A fully reconfigurable series-parallel photovoltaic module for higher energy yields in urban environments

Photovoltaic modules in the urban environment are very often exposed to uneven illumination conditions. The electrical interconnection between solar cells in a photovoltaic module limits the power that a solar module can generate under partial shading conditions. In this article, we introduce a PV module that is able to dynamically reconfigure the interconnection between its solar cells to minimise conduction and mismatch losses according to the irradiance distribution on its surface. Using an accurate simulation framework, it is determined that a reconfigurable PV module can generate over 12% more energy than a standard PV module with fixed topology and six bypass diodes, and as much energy as a fixed series-parallel module with six parallel strings, but at significantly lower currents. Simulation results are validated experimentally using a photovoltaic module with six reconfigurable blocks of cells controlled by a switching matrix on a high-performance solar flash simulator.

High-speed optical sampling system combined with cavity-less pulse source

High-speed optical sampling can overcome the limitation faced by electronic systems, such as bandwidth and precision. In this work, a 4-fold optical sampling time-parallelization is combined with a cavity-less 10GHz pulse source. The 4-fold sampling time-parallelization is based on a 1x4 optical switching matrix. Three dual-outputs Mach-Zehnder modulators (D-MZM) in cascaded configuration are included. Instead of a 10GHz repetition mode-locked laser (MLL), a cavity-less 10GHz pulse source is designed and used to provide the 10GHz modulated pulse as used in the switching matrix, which consists of a Mach-Zehnder amplitude modulator (MZM), a phase modulator (PM) and a highly dispersive optical fiber. We demonstrate a 4-fold sample time-parallelization with a high repetition rate up to 10GHz and 2.5GHz per channel, also with a signal-to-noise ratio (SNR) of 30dB, and combined with a 10GHz cavity-less pulse source with a pulsewidth of 9ps, which can be used into the advancements in radar and telecommunication systems.

Down-Scalable and Ultra-fast Memristors with Ultra-high Density Three-Dimensional Arrays of Perovskite Quantum Wires.

With strikingly high speed, data retention ability and storage density, resistive RAMs have emerged as a forerunning nonvolatile memory. Here we developed a Re-RAM with ultra-high density array of monocrystalline perovskite quantum wires (QWs) as the switching matrix with a metallic silver conducting pathway. The devices demonstrated high ON/OFF ratio of ∼107 and ultra-fast switching speed of ∼100 ps which is among the fastest in literature. The devices also possess long retention time of over 2 years and record high endurance of ∼6 × 106 cycles for all perovskite Re-RAMs reported. As a concept proof, we have also successfully demonstrated a flexible Re-RAM crossbar array device with a metal-semiconductor-insulator-metal design for sneaky path mitigation, which can store information with long retention. Aggressive downscaling to ∼14 nm lateral dimension produced an ultra-small cell effectively having 76.5 nm2 area for single bit storage. Furthermore, the devices also exhibited unique optical programmability among the low resistance states.

Cognitive Antenna Selection for Automotive Radar Using Bobrovsky-Zakai Bound

Automotive imaging radars require high angular resolution which can be achieved by a large antenna aperture. In order to obey Nyquist spatial sampling rate, a large number of array elements and receive channels is required. In practice, this solution results in a prohibitively high cost and complexity. This work proposes a new cognitive receiver configuration, in which a large number of sensor array elements is connected to a small number of receive channels via a switching matrix. The state of the switching matrix is sequentially updated using information from previous observations and prior information. According to the proposed scheme, denoted as cognitive antenna selection (CASE), the state of the switching matrix is obtained by the minimization of conditional Bayesian bounds on the mean-squared-error of the direction-of-arrival estimate. We show that the Bayesian Cramér-Rao bound (BCRB) is an inappropriate optimization criterion since it ignores the effect of ambiguity. This work proposes the Bobrovski-Zakai bound (BZB), which accounts for the effect of ambiguity, as a criterion for cognitive antenna selection. The performance of the proposed CASE-BZB approach is evaluated via simulations in single and multiple target scenarios. It is shown that the CASE-BZB outperforms random and linear switching algorithms both asymptotically and in the threshold region.

Switching Matrix Enabled Optimal Topology Reconfiguration for Maximizing Power Generation in Series–Parallel Organized Photovoltaic Systems

Mismatch losses (ML) problem can directly reduce the power generation of a photovoltaic (PV) array as well as complicate maximum power point tracking (MPPT) algorithms by causing multiple peaks to appear in the P-V characteristic. Hence, PV array reconfiguration techniques have become highly popular to minimize the ML of PV arrays. In this article, an optimal dynamic topology reconfiguration method based on a switching matrix is presented for series–parallel (SP) interconnected PV array to mitigate the ML, thereby maximizing the power generation of the PV array. The design of the switching matrix is presented that enables each string of the PV array to be divided into two sections to carry out the efficient dynamic topology reconfiguration with improved flexibility and scalability. The proposed reconfiguration method is assessed and compared with the SP scheme and the recently developed cross diagonal view method. The effectiveness of the proposed solution for the TCT scheme is also confirmed through simulation experiments. The numerical results indicate that the multiple peaks on P-V curves can be reduced and MPPT can be implemented with a simple control algorithm. Additionally, the maximum power generation improved by 20.13% and 14.39% on average compared to the SP scheme and TCT scheme, respectively, for different mismatch conditions of partial shading and random PV module failures.

Design, simulation and testing of an array of nano electro mechanical switches (NEMS)

Electro mechanical switches used for multi-purposs applications with ultra small size in nano meter scale, operating in very small voltage in millivolts, approximately zero leakage current due to air gap separation between electrodes with three terminals that easy to control it. Nano electro mechanical switches are electronic switches similar to those used by conventional semiconductor switches in application as they can be used as relays, logic devices. The basic principle of nano electro mechanical switches is electronic switches operation is fundamentally different from semiconductor switches. They have many advantages over conventional semiconductor switches such as low-power digital logic applications, ability to work with very small voltage signals for low dynamic energy consumption, and durability against hostile environments such as high temperatures and radiation contaminated spaces. In this article, we will design, implement, and test a matrix of nano electro mechanical switches by on line test using the superposition theory. The simulations of these switches were implemented using the MATLAB-Simulink and ORCAD Pspice environments. Also, controlling the flow of current was achieved by means of a nanometer movement to make or break the physical contact between the electrodes.

Inhibition of ERK 1/2 kinases prevents tendon matrix breakdown

Tendon extracellular matrix (ECM) mechanical unloading results in tissue degradation and breakdown, with niche-dependent cellular stress directing proteolytic degradation of tendon. Here, we show that the extracellular-signal regulated kinase (ERK) pathway is central in tendon degradation of load-deprived tissue explants. We show that ERK 1/2 are highly phosphorylated in mechanically unloaded tendon fascicles in a vascular niche-dependent manner. Pharmacological inhibition of ERK 1/2 abolishes the induction of ECM catabolic gene expression (MMPs) and fully prevents loss of mechanical properties. Moreover, ERK 1/2 inhibition in unloaded tendon fascicles suppresses features of pathological tissue remodeling such as collagen type 3 matrix switch and the induction of the pro-fibrotic cytokine interleukin 11. This work demonstrates ERK signaling as a central checkpoint to trigger tendon matrix degradation and remodeling using load-deprived tissue explants.

An Ultra-Wideband Antenna With Low Dispersion for Ground Penetrating Radar System

An Ultra-wideband Antenna with funnel-shaped slots and rectangle copper sheets loaded was proposed for ground penetrating radar applications covering the frequency range from 250 MHz to 780 MHz. The performances of the proposed antenna were modeled and optimized by using finite difference time domain methods and measured in both time and frequency domains. The proposed antenna had a bandwidth of 102.9% with voltage standing-wave ratio (VSWR) < 2 and a pick gain over 3 dBi, even when the antenna was bent according to the shape of antenna carrier. In addition, a reconfiguration antenna array with switching matrix, which could be loaded up to 12 antennas, was proposed, where the scanning strategy could be programmed according to the requirements. On this basis, the VSWR of antenna array with and without switching matrix were compared, and the performances of bent and non-bent antenna were also compared in the far-field region. For the radiation pattern, the back-lobe level of bent antennas in E-plane was much lower than non-bent antennas, and the main-lobe of bent antennas in H-plane were rotated. For the peak realized gain, although the antenna gain decreases with increasing frequency, the rate of decline of bent antenna gain is significantly less than that of non-bent antenna gain. Finally, the fabricated antennas could be loaded on a SFCW-GPR system for detecting the depth of cable wells under the road.

Diffusive and Drift Halide Perovskite Memristive Barristors as Nociceptive and Synaptic Emulators for Neuromorphic Computing

AbstractWith the current research impetus on neuromorphic computing hardware, realizing efficient drift and diffusive memristors are considered critical milestones for the implementation of readout layers, selectors, and frameworks in deep learning and reservoir computing networks. Current demonstrations are predominantly limited to oxide insulators with a soft breakdown behavior. While organic ionotronic electrochemical materials offer an attractive alternative, their implementations thus far have been limited to features exploiting ionic drift a.k.a. drift memristor technology. Development of diffusive memristors with organic electrochemical materials is still at an early stage, and modulation of their switching dynamics remains unexplored. Here, halide perovskite (HP) memristive barristors (diodes with variable Schottky barriers) portraying tunable diffusive dynamics and ionic drift are proposed and experimentally demonstrated. An ion permissive poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate interface that promotes diffusive kinetics and an ion source nickel oxide (NiOx) interface that supports drift kinetics are identified to design diffusive and drift memristors, respectively, with methylammonuim lead bromide (CH3NH3PbBr3) as the switching matrix. In line with the recent interest on developing artificial afferent nerves as information channels bridging sensors and artificial neural networks, these HP memristive barristors are fashioned as nociceptive and synaptic emulators for neuromorphic sensory signal computing.

Artificial Intelligent Algorithm to control Circuits Structuring of Flexible remote Experiments in Engineering within a Switching Matrix Architecture

This paper presents the development of an artificial intelligent algorithm to control circuits structuring of flexible remote experiments in engineering fields of electronics and electricity within a switching matrix architecture. In addition, this paper presents a technical analyze and characterization of VISIR system to point itsadvantages and its inconveniences.The developedartificial intelligent algorithm controlsthe interconnections between electrical and electronic components and monitorsthe power supplying and measurements conducting onVISIR system.We also developed an electronic board to provide the physical possibility of connecting any component to any other component on VISIR’s switching system, and thereby manifesting a switching matrix architecture within VISIR. The developed switching matrix architecture and the developed algorithm enable to have flexible remote experiments in engineeringfields of electronics and electricitywhile havingresilient control on circuits structuring for e-learning purposes.Inaddition, they open the way to havemore circuit combinations of experiments by offering the possibility of connecting any component to any other componentwhile respecting the electrical limits of current and voltage.

An MMTES algorithm for dynamic photovoltaic array reconfiguration to enhance power output under partial shading conditions

Partial shading is a severe impediment to the effective use of photovoltaic systems. It will lead to performance degradation in the photovoltaic system. This work proposes a maximum–minimum tier equalisation swapping reconfiguration algorithm for total-cross-tied connection under shading conditions. The proposed reconfiguration algorithm uses a switch matrix to alter the interconnection of modules in a photovoltaic array. The switch matrix dynamically modifies the connections based on the equalisation of tier irradiance. This algorithm applies to the symmetrical and asymmetrical photovoltaic array. Further, simulation studies show the efficacy of the proposed algorithm by minimising the multiple peaks and enhancing the output power compared with the traditional total-cross-tied configuration. The performance of experimental tests ascertains the feasibility of the proposed method.

Comparative analysis of two-step GA-based PV array reconfiguration technique and other reconfiguration techniques

Photovoltaic (PV) plants can be exposed to partial shading, which reduces the energy production and causes multi-peaks to form in the Power-Voltage (P-V) curve. As a result, the row currents of the PV modules will not be constant. Several techniques have been proposed to overcome partial shading, such as the static and dynamic reconfiguration techniques, with both aiming to reduce the difference in the row currents to improve energy production. Minimization of the row current via static techniques requires laborious work and extra wiring. On the other hand, dynamic techniques require an extensive monitoring system to support different tasks. Therefore, to improve the power generated from the PV array, this paper suggests a new reconfiguration technique for PV panels using Genetic algorithm (GA) and two main reconfigurable steps based on a switching matrix. In this technique, only the electrical connections of the PV panels are changed while its physical location remains unchanged. To verify the effectiveness of the proposed reconfiguration technique, the system was simulated and tested using MATLAB/SIMULINK software, with four shading patterns. The results were compared with other reconfiguration techniques, namely TCT configuration, competence square (CS), SuDoKu, two-phase array reconfiguration, Genetic algorithm (GA), Particle Swarm Optimization (PSO), and Modified Harris Hawks Optimization (MHHO). The performance of each shading case was also analyzed. Also, a comparative study on performance analysis in real-time application was carried out for each shading pattern. The results prove the superiority of the proposed technique over other techniques for overcoming partial shading.

A Novel Active Equalization Method for Series-Connected Battery Packs Based on Clustering Analysis With Genetic Algorithm

Battery pack performance is the main concern for electric vehicles and energy storage systems. However, charge imbalance is inevitable due to inconsistent manufacturing techniques and environmental conditions. Charge imbalance reduces the power performance and available energy of battery packs. Hence, it is necessary to perform battery equalization. This article proposes an active equalization circuit and a novel equalization strategy to achieve energy redistribution. A bidirectional equalization topology consisting of a forward transformer and switch matrix is proposed first. Then, an innovative equalization strategy based on clustering analysis and genetic algorithm (GA) is developed. Clustering analysis is introduced to identify the target cells to be balanced. To further increase the speed of the equalization process, GA is employed to optimize the classification results. Finally, a series of experiments were conducted to confirm the effectiveness of the proposed topology and the strategy. Both the simulation and experimental results validate that the proposed equalization strategy not only improves the inconsistency but also increases the equalization speed. In practical battery pack experiments, the pack capacity is improved by 16.84% after equalization, and the equalization time is decreased by 23.8% using the proposed method.

On optimization of of network traffic according to the communication matrix

The article is devoted to the search for solutions to optimize multiservice network traffic taking according the switching matrix by increasing the capabilities of network equipment with restrictions on their number with the ability to implement the algorithm as a Virtual Network Function for a Software-Defined Network. It is assumed that the networks are represented by an undirected complete connected planar graph.

Adaptive Switch Matrix for PV Module Connections to Avoid Permanent Cross-Tied Link in PV Array System Under Non-Uniform Irradiations

In this paper, the significance of cross-tied link between the solar photovoltaic (PV) modules in an array during partial shading conditions (PSCs) is introduced. In order to conduct a detailed analysis, twenty numbers of 20W PV modules ( 4×5) are arranged in a series-parallel (SP) configuration. The change in the pre-arranged SP configured PV array is implemented using a cross-link matrix switch between parallels based on shadow patterns. The switch matrix based modified PV array configuration is called Adaptive-cross-tied (A-CT) configuration. An embedded system based adaptive switch matrix (ASM) controller is developed to control the cross-linking connections between the PV modules under the PSCs to improve global maximum power. In addition, a performance analysis is carried out and compared all PV modules arranged in conventional SP and A-CT configurations. Moreover, realistic shadow test cases are under consideration to characterize current-voltage (I-V) and power-voltage (P-V) characteristics. The output power of the PV array decreases as well as the P-V curves show multiple power maxima points., such as the local maximum power point (LMPP) and the global maximum power point (GMPP). LMPP and GMPP locations, mismatch loss (ML), enhanced fill factor (FF), decreased power loss (PL) and performance ratio (PR) are indicators of performance during experimental and MATLAB/Simulink studies.

Fault Estimation for Continuous-Time Markovian Jump Systems: An Auxiliary System Approach

This paper addresses the fault estimation problem for continuous-time Markovian jump systems (MJSs). Because the system is stochastic but the estimated fault is deterministic, it is not easy to study the fault estimation problem directly. To overcome this contradiction, an auxiliary system approach is proposed, where a deterministic intermediate variable is constructed by taking expectation on some stochastic variables and the error state and fault are also estimated. Moreover, based on some novel enlarging techniques, more general estimation situations about partially unknown transition rate matrix and semi-Markovian switching are firstly considered. Linear matrix inequality (LMI) conditions are given to guarantee the error states uniformly bounded. Two numerical examples are presented to illustrate the utility and advantage of established methods.

FIRST MICROWAVE TOMOGRAPHY APPROACH TOWARDS A TRULY NONINVASIVE, PAIN-FREE AND WEARABLE BLOOD GLUCOSE MONITORING DEVICE

Despite the advancements in the field of glucose monitoring sensors, the development of noninvasive, wearable, continuous and comfortable systems is still a real challenge. New technologies are required for noninvasive, continuous and effective measurements remaining discreet, painless, comfortable to the patient and avoiding additional costs. This article presents a truly noninvasive microwave tomography prototype designed for glucose monitoring. The system is based on an array of dipole antennas placed in a circular configuration. The transmitted field data are collected using a switch matrix connected to a vector network analyzer. A heterogeneous 3-D arm model and a 3-D electromagnetic solver have been used to model the human arm and to characterize the system. Blood electromagnetic properties are affected by the glucose concentration, a promising correlation between the dielectric properties of blood and glucose level should be investigated. By simulating the antenna array on the arm phantom, the characteristics of the S-parameters were interesting at the frequencies of interest. The transmission coefficient amplitude decreases as the dielectric constant decreases from 63 to 40, and the conductivity increases from 1.5 S/m to 3.5 S/m. For each value of dielectric properties, a given transmission coefficient value can be clearly identified. Experimental measurements validated the arm phantom and confirmed the relationship between the response of the system and the dielectric properties of blood tissue. The armband sensor is designed as an inexpensive, noninvasive, and light weight device suitable for all patients with a high level of discretion. This work, under optimization for preclinical and clinical testing, demonstrates the proof of concept of an innovative microwave tomography system for noninvasive glucose monitoring. Compared to studies with a similar aim, this research may achieve distinct advances and offers promising hope in the field of noninvasive glucose sensors.