Reconfiguration Scheme Research Articles

Self-propelling colloids with finite state dynamics

Endowing materials with the ability to sense, adapt, and respond to stimuli holds the key to a progress leap in autonomous systems. In spite of the growing success of macroscopic soft robotic devices, transferring these concepts to the microscale presents several challenges connected to the lack of suitable fabrication and design techniques and of internal response schemes that connect the materials' properties to the function of the active units. Here, we realize self-propelling colloidal clusters which possess a finite number of internal states, which define their motility and which are connected by reversible transitions. We produce these units via capillary assembly combining hard polystyrene colloids with two different types of thermoresponsive microgels. The clusters, actuated by spatially uniform AC electric fields, adapt their shape and dielectric properties, and consequently their propulsion, via reversible temperature-induced transitions controlled by light. The different transition temperatures for the two microgels enable three distinct dynamical states corresponding to three illumination intensity levels. The sequential reconfiguration of the microgels affects the velocity and shape of the active trajectories according to a pathway defined by tailoring the clusters' geometry during assembly. The demonstration of these simple systems indicates an exciting route toward building more complex units with broader reconfiguration schemes and multiple responses as a step forward in the pursuit of adaptive autonomous systems at the colloidal scale.

Modeling and Analysis of Different Reconfiguration Strategies for Virtual Network Function Placement and Chaining with Service Classes Identification

The Virtual Network Function Placement and Chaining problem (VNF-PC) is an important part of the Network Functions Virtualization (NFV) based-technologies implementation. VNF-PC problem focuses on the allocation of customer demands on the Substrate Network. Aiming to evaluate the impact of diverse modeling, various reconfiguration strategies based on implicit steps in solving the VNF-PC are proposed: resizing virtual network instances, re-routing chaining, and repositioning Network Functions (NF) instances on different servers. In addition, this work analyzes, compares, and discusses the advantages and disadvantages of each proposed reconfiguration strategy in an online scenario. Traditionally, VNF-PC solutions from literature process requests generated at random and do not take into account real-world demands. Complementing the analyses of reconfiguration strategies, works from the literature are surveyed to identify commonly used Network Services (NS). Following that, these NS are classified into service classes, and used to generate realistic requests to be mapped in the experimental stage of the reconfiguration approaches. The experiments are conducted using realistic requests and a real-world network topology. An Integer Linear Programming model is used to process the requests. Simulations show that repositioning NF instances can generate up to 25% more profit than reconfiguring only the VNF instances, but the processing time increases by up to 99.99%. On the other hand, resizing virtual network instances and re-routing the chaining had no significant impact on runtime.

Fully Automatic In-Situ Reconfiguration of Optical Filters in a CMOS-Compatible Silicon Photonic Process

Automatic reconfiguration of optical filters is the key to novel flexible RF photonic receivers and Software Defined Radios (SDRs). Although silicon photonics (SiP) is a promising technology platform to realize such receivers, process variations and lack of in-situ tuning capability limit the adoption of SiP filters in widely-tunable RF photonic receivers. To address this issue, this work presents a first ‘in-situ’ automatic reconfiguration algorithm and demonstrates a software configurable integrated optical filter that can be reconfigured on-the-fly based on user specifications. The presented reconfiguration scheme avoids the use of expensive and bulky equipment such as an Optical Vector Network Analyzer (OVNA), does not use simulation data for reconfiguration, reduces the total number of thermo-optic tuning elements required, and eliminates several time-consuming configuration steps as in the prior art. This makes this filter ideal in a real-world scenario where the user specifies the filter center frequency, bandwidth, required rejection, and filter type (Butterworth, Chebyshev, etc.), and the filter is automatically configured regardless of process, voltage, and temperature (PVT) variations. We fabricated our design in AIM Photonics' Active SiP process and have demonstrated our reconfiguration algorithm for a second-order filter with a 3 dB bandwidth of 3 GHz, 2.2 dB insertion loss, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&gt;$</tex-math></inline-formula> 30 dB out-of-band rejection using only two reference laser wavelength settings. Since the filter photonic integrated circuit (PIC) is fabricated using a CMOS-compatible SiP foundry, the design is manufacturable with repeatable and scalable performance suited for its integration with electronics to realize complex chip-scale RF photonic systems.

Resilience-oriented network reconfiguration strategies for community emergency medical services

Resilience-oriented network reconfiguration strategies for community emergency medical services

Robust reconfiguration strategies for maximum output power from large-scale photovoltaic arrays under partial shading conditions

Extraction of maximum power from large scale solar photovoltaic power systems is the most challenging and demanding research in the current scenario. Solar photovoltaic panels are highly susceptible to a phenomenon known as partial shading. Partial shading increases mismatch losses and reduces the output of the solar photovoltaic system The output reduction in the partially shaded array is proportional to the shaded area, shaded panel’s placement within the array, panel connections, shade geometry, etc. There are several approaches for reducing Partial shading effects in the literature. The most efficient approach to mitigating the mismatch losses due to Partial shading in large-scale solar photovoltaic systems is the reconfiguration technique, which distributes shaded panels more evenly and increases the maximum power output. The current work utilizes a set of reconfiguration rules for selecting the location of shaded panels within an array that allows for multiple reconfiguration options. The results show that the proposed reconfiguration has obtained an improved Performance enhancement ratio of 25% in one shading pattern i.e. short wide shading, Performance enhancement ratio of 6.4% in short narrow and centre shading and Performance enhancement ratio of 5.9% in long narrow shading. The proposed reconfiguration was found to be the most suitable, simple, and cost-effective solution for large size of solar photovoltaic system under all shading conditions.

Defect Reconfiguration in Hole-Doped PbSe via Minute Te Doping for Significantly Enhanced Thermoelectric Performance

Rich defects near the percolation threshold of dilute solid solutions are of fundamental interest to thermoelectric research. Sn-substituted Pb0.98Na0.02Se (1 mol %) is a typical example that demonstrates how various defects induce intriguing transport phenomena. Unfortunately, the presence of Pb vacancies severely degrades the carrier mobility of samples, and the thermoelectric figure of merit ZT is only marginally improved. In this study, we show that Pb vacancies are effectively inhibited by a facile defect reconfiguration strategy. This is achieved by doping a dilute amount of Te at Se sites of Pb0.97Sn0.01Na0.02Se, where the interstitial Sn ions are pulled back to Pb sites as revealed by the X-ray photoelectron spectroscopy analysis and the positron annihilation test. Consequently, Pb vacancies get occupied, and the room temperature carrier mobility is remarkably recovered from 2.8 to 70 cm2 V–1 s–1 upon 3 mol % Te doping. Moreover, Te doping reinforces phonon scattering by strain and mass field fluctuations. The lattice thermal conductivity at 300 K goes down to ∼1.7 W m–1 K–1 for Pb0.97Sn0.01Na0.02Se0.94Te0.06, which is ∼32% lower than that of the Pb0.97Sn0.01Na0.02Se control sample. Altogether, the average ZT value of Pb0.97Sn0.01Na0.02Se between 300 and 773 K is doubled upon 6 mol % Te doping.

Provisioning network slice for mobile content delivery in uncertain MEC environment

Network Slicing (NS) and Mobile Edge Computing (MEC) are recognized as a promising paradigm for mobile Content Delivery Network (CDN) by instantiating Virtual Network Functions (VNFs) on MEC platforms. Mobile network exhibits intrinsic dynamics, where user requests patterns vary in time and space due to human behaviors. The requirements and distribution of users are arbitrary spatio-temporal stochastic variables, which makes the deployment and reconfiguration of a CDN slice a challenging task. In this work, by adopting a periodical reconfiguration strategy, we consider a CDN slice system which operates in discrete time intervals. Within each time interval, we formalize the CDN-MEC-VNFs Planning (CMVP) problem based on uncertain programming to tackle the dynamic and uncertain mobile network environment, where user requests are treated as random variables with arbitrary pattern. Then, we propose a data-driven and learning-based algorithm which integrates Stochastic Simulation (SS), Deep Neural Networks (DNN) and meta-heuristic algorithm to determine the provisioning of the CDN slice from historical user requests information. The practicability of the proposed mechanism in offline training and online running are also discussed. Finally, we conducted intensive real-trace driven simulations to demonstrate the effectiveness of our approach on planning CDN slice with higher QoS under dynamic system environment and arbitrary user requests by comparing towards several baselines.

Automatic PV Array Reconfiguration under Partial Shading Conditions

Photovoltaic (PV) arrays have been recognized as one of the main clean renewable sources of electrical energy. In practice, PV arrays are subject to unavoidable non-uniform partial shading (PS) due to clouds, buildings, dust, etc. PS causes the hot spot problem, mismatch losses, and output power degradation. A widely used approach to mitigate the effect of PS is dynamic reconfiguration, where, the interconnection of PV panels is modified according to the shading condition to achieve maximum output. Dynamic reconfiguration techniques use sensors, a programmable controller, and a switch matrix for optimal operation. However, they have drawbacks such as system complexity and scalability issues. For instance, reducing the number of switches limits the flexibility of the reconfiguration algorithm. In this paper, an automatic dynamic reconfiguration scheme is proposed in which PV panel irradiation activity controls the interconnection of switches, without the need for a programmable controller. A modular building block is proposed from which easily scalable PV arrays can be constructed in a hierarchical manner. Experimental and analytic results have verified the effectiveness of the proposed reconfiguration scheme.

Reconfiguration strategy for fully actuated translational cable-suspended parallel robots.

In Cable-Suspended Parallel Robots (CSPRs), reconfigurability, i.e., the possibility of modifying the position of the cable connection points on the base frame, is particularly interesting to investigate, since it paves the way for future industrial and service applications of CSPRs, where the base frame can also be replaced by mobile agents. This report focuses on fully actuated Translational Reconfigurable CSPRs (TR-CSPRs), i.e., reconfigurable CSPRs with a point mass end-effector driven by three cables. The objective of the work is twofold. First, it is shown that the Wrench Exertion Capability (WEC) performance index can be exploited to identify the configurations of the cable connection points optimizing a task-related performance in a single point or throughout the workspace, and hence to implement a workspace analysis. Then, by referring to the case of a TR-CSPR with a single reconfigurable connection point and in quasi-static working condition, an analytical approach is provided to reconfigure the robot while executing a task to avoid one of the paramount problems of cable robots: cable slackness. Brought together, the two contributions allow defining a reconfiguration strategy for TR-CSPRs. The strategy is presented by applying it to a numerical example of a TR-CSPR used for lifting and moving a load along a prescribed path: the use of the WEC allows analyzing the workspace and predicting if robot reconfigurability makes it possible to pass quasi-statically along all the points of a given path; then reconfigurability is exploited to avoid cable slackness along the path.

High-Gain Bidirectional LCLC Resonant Converter With Reconfigurable Capability

A reconfigurable gain circuit is proposed for an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCLC</i> resonant converter with bidirectional capability considering wide varying redox flow battery source. A suitable hybrid control scheme for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCLC</i> resonant converter with secondary synchronous rectifier is proposed in this work. The proposed reconfigurable circuit enables to configure secondary bridge as an active voltage doubler, full-bridge circuit during forward power transfer mode and reverse power transfer mode, respectively. The reconfigurability helps significantly to design a transformer with lower secondary turns and achieve desired high gain. The reduced transformer secondary turns result in reduced transformer parasitics. The presence of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCLC</i> resonant tank helps to provide the additional gain; the hybrid control scheme ensures zero-voltage switching turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> for the primary, and secondary synchronous <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfets</small> throughout the operating range. The proposed converter is analysed using fundamental harmonic approximation. The proposed reconfigurable gain circuit and hybrid control scheme is verified experimentally for an 800 V/1 kW hardware prototype fed from 24 to 54 V input.

Fast reconfiguration method of low-carbon distribution network based on convolutional neural network

The existing meta-heuristic distribution network reconfiguration (DNR) algorithm has excellent optimization ability through iteration. However, it is difficult to realize the large-scale fast calculation and online real-time response of DNR solution. In order to improve the security and low-carbon economy of distribution network, this paper proposes a fast reconfiguration method of distribution network based on convolutional neural network (CNN). Taking IEEE 33 system and 185 node system as examples, the effectiveness of the proposed method is verified. The reasons why the proposed method can achieve better results are as follows: By mining the historical data of distribution network, the corresponding relationship between load mode (LM) and its optimal topology is established. For a load mode in actual operation, the reconfiguration scheme can be quickly obtained according to the established corresponding relationship. Thus, iterative calculation is avoided and computational efficiency is improved. A multi-branch CNN model is established based on the distribution network structure, and an inception module is introduced into CNN to improve the ability of CNN to extract data features. This model can reduce the dependence on the specific distribution network structure and is easy to expand.

A review of PV array reconfiguration techniques for maximum power extraction under partial shading conditions

Partial shading is a significant obstacle to the effective use of photovoltaic (PV) systems because it reduces output power significantly. The output power reduction is not proportional to the shaded area but rather depends on the PV array configuration/reconfiguration and shadowing pattern. PV array reconfiguration is one of the most effective solutions for overcoming the adverse effects of partial shading in PV systems. The main objective of PV array reconfiguration strategies is to disperse shades consistently over the entire area of the PV array to reduce the adverse impact of partial shading situations. This paper provides an in-depth examination of the significant existing PV array reconfiguration methods used to address the problem of partial shading. The various methods are evaluated and compared based on their techniques, benefits, and drawbacks. This work is an interesting reference for researchers in the field and a simple guide for beginners on PV array reconfiguration.

Path Planning Method of Unmanned Surface Vehicles Formation Based on Improved A* Algorithm

Unmanned surface vehicle (USV) formation is a hot topic of current research. Path planning is the core technology for USV formation. This paper focuses on a USV formation path planning problem considering kinetic constraints. Firstly, an improved A* algorithm is proposed to solve the point-to-point path planning of a USV considering kinetic constraints. In this algorithm, the yaw constraint is introduced on top of the position constraint to extend the state space of the USV to three dimensions, and the convergence speed is accelerated by building a heuristic map. The dynamics model of the USV is used to generate the minimum trajectory elements to ensure that the path conforms to the kinetic constraints. Secondly, the mathematical model of USV formation based on the virtual structure method is established, and the path planning scheme of formation navigation and formation reconfiguration is given according to the improved A* algorithm. Finally, we carry out a USV model identification experiment for SL900 USV and simulation experiments based on the model. The experimental results show that the output path of the proposed method is smoother compared with the traditional method. This method can provide a globally safe path with kinetic constraints for USV formation navigation and formation reconstruction.

High-stable and reconfigurable photonic generation of radio-frequency arbitrary waveforms with multi-tone inputs

Conventional temporal pulse shaping (TPS) for radio frequency (RF) arbitrary waveform generation (RF AWG) based on the Fourier transform relation between the input–output waveform pair requires the electronic AWG to generate RF input signal, which greatly limits the output waveform diversity due to the relative low sampling rate and bit resolution of electronic AWG, i.e., high-fidelity square waveforms are hard to be achieved since high-resolution broadband Sinc input signals are difficult to be generated by current commercial electronic AWGs. The approaches based on TPS with phase modulation incorporating with iterative algorithms can relatively improve the waveform diversity by applying the optimal phase information. However, time-consuming iterative algorithms significantly restrict the waveform reconfigurability, i.e., desired RF waveforms cannot be generated in real-time. We propose a novel high-stable and reconfigurable RF AWG scheme with multi-tone inputs, which aims to improve the output waveform diversity with simple manipulation and high stability. In our design, any desired RF waveform can be achieved in real-time by simply adjusting the power values of multi-tone inputs. A proof-of-concept experiment was implemented, which fully verified the feasibility of the approach. The system performance in terms of output waveform stability was investigated in detail. As no electronic AWG is employed and no iterative algorithms are required, the proposed design provides a promising solution for high-performance reconfigurable photonic-based RF arbitrary waveforms generation.

Aerospace industrial benchmarking and fault-tolerant control design using NARX model-based observer

This paper proposes a fault tolerant control (FTC) design with a fault detection (FD) scheme for oscillatory failure cases (OFC) within the framework of “The Joint Airbus-Stellenbosch University Industrial Benchmark.” The FD scheme consists of an observer using “Nonlinear Autoregressive models with eXogenous input” (NARX) model, a signal processing part, and an FD algorithm. The proposed FTC design smoothly switches controllers by adjusting weights according to a sigmoid function using a reconfiguration scheme. The parameters in both schemes are optimized by grid search based on the metrics set to evaluate performance. These schemes have the advantage of the ease of industrial use because they have a simple structure, and parameters can be tuned in a systematic way. Simulation results show that the proposed FD scheme's ability to detect OFC meets the benchmark's prescriptions regardless of the defined turbulence or load factor input. The robustness of the proposed FD scheme was evaluated using a Monte Carlo method by varying the parameters of the actuator model to confirm the limit value of the OFC amplitude that can be robustly detected.

Fault Tolerant Control via Input-Output Linearization Method for LED-Driver Using a Boost Converter

This paper proposes a method based on an input-output linearization controller with a nonlinear adaptive observer, in order to achieve both an effective light-emitting diode (LED) current tracking and an actuator fault tolerant controller strategy for a LED-driver, using a boost converter. The partial fault is presented as a Loss of Effectiveness (LoE) in the embedded control target by considering that it generates a faulty Pulse-Width Modulation (PWM) signal. Also, faults of energy storage components in the power system are considered as actuator partial faults. An internal stability analysis is presented to ensure the feasibility of the nonlinear controller design. The nominal feedback controller is able to compensate for the nonlinearity of the system exactly, thus yielding a linear control loop. Furthermore, a nonlinear adaptive observer is considered for fault estimation. When the actuator fault is detected and estimated correctly, fault accommodation and reconfiguration strategies are performed to reduce the fault’s effect. The controller and observer gains are tuned using genetic algorithm techniques to have a desired closed-loop and fault estimation error response. Finally, simulations results are done in order to illustrate the effectiveness of the proposed methodology.

Partial State Feedback MRAC Based Reconfigurable Fault-Tolerant Control of Drag-Free Satellite With Bounded Estimation Error

Aiming at the ultra-precision and ultra-stable requirements of drag-free control in space detection missions, a multivariable model reference adaptive control (MRAC) scheme is proposed in this paper based on partial observation state, to provide adaptive suppression of uncertain disturbances and improve detection accuracy. The MRAC scheme utilizes model output matching with partial state containing uniform and bounded observation error, and estimates the unknown state parameters through the adaptive law and high-frequency gain decomposition. In response to the actuator bias fault of the drag-free satellite, a set of state error iterative convergence sequence in the actuator loop is established based on the sequence Lyapunov analysis, which is further introduced into the reconfiguration control input to achieve the fault-tolerant target without changing the nominal controller. Through the Lyapunov stability analysis, the convergence of the closed-loop system states in the presence of actuator faults and observation errors is obtained. Numerical simulation results for a 6-DOF drag-free control system demonstrate the effectiveness of the proposed MRAC-based reconfigurable fault-tolerant control scheme.

A New Family of Reconfigurable Waveguide Filters and Diplexers for High-Power Applications

In this paper, we discuss how the use of the recently developed modified tuning pin (MTP) can be extended to the design of filters and diplexers implemented in rectangular waveguide, that can be reconfigured in a number of discrete states, and that can be used in high-power payloads. As an application example, the design of two reconfigurable filters and a reconfigurable diplexer is fully described. The high-power behavior of these components (in particular, with respect to corona and multipaction effects) is also studied in detail, in order to demonstrate that the structures that we discuss can operate correctly under high-power conditions. Furthermore, comparisons between simulations and measurements of several prototypes are also included, showing an excellent agreement between simulated and experimental data, thereby fully validating both the design approach and the filter reconfiguration strategy.

Fault Diagnostics for Oscillatory Failure Case in Aircraft Elevator Servos

Oscillatory Failure Case (OFC) is a characteristic sinusoidal fault that propagates through control surfaces and actuator servo loops of commercial aircrafts that originates from spurious sensor measurements and actuator commands. The goal of this work is to detect such faults of unknown amplitudes and frequencies in the presence of turbulence. The fault detection scheme employs a graph-theoretic approach that uses a structural model of the aircraft's longitudinal dynamics and the servo actuators to determine residuals for OFC fault detection and isolation. A smooth controller reconfiguration strategy is proposed to switch between a nominal control law and a degraded alternate control law which utilizes sensor measurement feedback as well as virtual sensors from a digital model of longitudinal cruising dynamics without affecting the controller structure and feedback loops.

Array Element Selection Strategies for Interference Suppression in Reconfigurable Tripole Antenna Array Systems

Compared with the scalar array, the polarization-sensitive array (PSA) possesses a more powerful anti-jamming ability in adaptive array processing. However, each antenna of the traditional PSA requires two or more radiofrequency (RF) front-ends, which results in proliferation in computational complexity and even configuration redundancy that has little impact on performance. Besides, the RF front-end is much more expensive than the antenna, making the cost extremely high when considering a large PSA. Therefore, it is essential to search for a PSA reconfiguration approach that utilizes fewer RF front-ends and can generate excellent interference rejection performance. In this work, we devise a new PSA reconfiguration strategy, termed dipole selection, to employ fewer dipoles and RF front-ends to acquire a high signal to interference plus noise ratio (SINR). And the strategy is implemented by controlling the RF switch between the RF front-end and the dipole. The polarization-spatial correlation coefficient (PSCC), characterizing the difference between desired signal and interference in the polarization-spatial domain, is proposed to analyze the effect of PSA reconfiguration on anti-interference performance. Subsequently, the problem of dipole selection is addressed with two proposed methods, named Quadratic-Over-Linear Fraction (QOLF) and Correlation Measurement Elimination (CME), respectively. Numerical and experimental simulation results demonstrate the correctness and effectiveness of the proposed strategy and approaches.