Specification and Verification of Dynamically Reconfigurable Systems Using Dynamic Linear Hybrid Automata

A dynamically reconfigurable system can change its configuration during operation, and studies of such systems are being carried out in many fields. In particular, medical technology and aerospace engineering must ensure system safety because any defect will have serious consequences. Model checking is a method for verifying system safety. In this paper, we propose the Dynamic Linear Hybrid Automaton (DLHA) specification language and show a method to analyze reachability for a system consisting of several DLHAs.

Reconfigurable Ultrasonic Testing System Development Using Programmable Analog Front-End and Reconfigurable System-on-Chip Hardware

Ultrasonic testing systems have been extensively used in medical imaging and non-destructive testing applications. Generally, these systems aim at a particular application or target material. To make these systems portable and more adaptable to the test environments, this study presents a reconfigurable ultrasonic testing system (RUTS), which possesses dynamic reconfiguration capabilities. RUTS consists a fully programmable Analog Front-End (AFE), which facilitates beamforming and signal conditioning for variety of applications. RUTS AFE supports up to 8 transducers for phased-array implementation. Xilinx Zynq System-on-Chip (SoC) based Zedboard provides the back-end processing of RUTS. The powerful ARM embedded processor available within Zynq SoC manages the ultrasonic data acquisition/processing and overall system control, which makes RUTS a unique platform for the ultrasonic researchers to experiment and evaluate a wide range of real-time ultrasonic signal processing applications. This Linux-based system is utilized for ultra-sonic data compression implementation providing a versatile environment for further development of ultrasonic imaging and testing system. Furthermore, this study demonstrates the capabilities of RUTS by performing ultrasonic data acquisition and data compression in real-time. Thus, this reconfigurable system enables ultrasonic designers and researchers to efficiently prototype different experiments and to incorporate and analyze high performance ultrasonic signal and image processing algorithms.

Channel Estimation for Reconfigurable Intelligent Surface Aided Multiuser Millimeter-Wave/THz Systems

It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.

Mission reliability modeling and evaluation for reconfigurable unmanned weapon system-of-systems based on effective operation loop

The concept of unmanned weapon system-of-systems(UWSoS)involves a collection of various unmanned systems to achieve or accomplish a specific goal or mission.The mission reliability of UWSoS is represented by its ability to finish a required mission above the baselines of a given mission.However,issues with heterogeneity,cooperation between systems,and the emergence of UWSoS cannot be effectively solved by traditional system reliability methods.This study proposes an effective operation-loop-based mission reliability evaluation method for UWSoS by analyzing dynamic reconfiguration.First,we present a new connotation of an effective operation loop by considering the allocation of operational entities and physical resource constraints.Then,we propose an effective operationloop-based mission reliability model for a heterogeneous UWSoS according to the mission baseline.Moreover,a mission reliability evaluation algorithm is proposed under random external shocks and topology reconfiguration,revealing the evolution law of the effective operation loop and mission reliability.Finally,a typical 60-unmanned-aerial-vehicle-swarm is taken as an example to demonstrate the proposed models and methods.The mission reliability is achieved by considering external shocks,which can serve as a reference for evaluating and improving the effectiveness of UWSoS.

Task-Oriented Topology System Synthesis of Reconfigurable Legged Mobile Lander Integrating Active and Passive Metamorphoses

To explore hostile extraterrestrial landforms and construct an engineering prototype,this paper presents the task-oriented topology system synthesis of reconfigurable legged mobile lander(ReLML)with three operation modes from adjusting,landing,to roving.Compared with our preceding works,the adjusting mode with three rotations(3R)provides a totally novel exploration approach to geometrically matching and securely arriving at complex terrains dangerous to visit currently;the landing mode is redefined by two rotations one translation(2R1T),identical with the tried-and-tested Apollo and Chang'E landers to enhance survivability via reasonable touchdown buffering motion;roving mode also utilizes 2R1T motion for good motion and force properties.The reconfigurable mechanism theory is first brought into synthesizing legged mobile lander integrating active and passive metamorphoses,composed of two types of metamorphic joints and metamorphic execution and transmission mechanisms.To reveal metamorphic principles with multiple finite motions,the finite screw theory is developed to present the procedure from unified mathematical representation,modes and source phase derivations,metamorphic joint and limb design,to final structure assembly.To identify the prototype topology,the 3D optimal selection matrix method is proposed considering three operation modes,five evaluation criteria,and two topological subsystems.Finally,simulation verifies the whole task implementation process to ensure the reasonability of design.

Differential Scheme for Reconfigurable Intelligent Surface-Based Spatial Modulation System

In this paper,a differential scheme is proposed for reconfigurable intelligent surface(RIS)assisted spatial modulation,which is referred to as RISDSM,to eliminate the need for channel state information(CSI)at the receiver.The proposed scheme is an improvement over the current differential modulation scheme used in RIS-based systems,as it avoids the high-order matrix calculation and improves the spectral efficiency.A mathematical framework is developed to determine the theoretical average bit error probability(ABEP)of the system using RIS-DSM.The detection complexity of the proposed RIS-DSM scheme is extremely low through the simplification.Finally,simulations results demonstrate that the proposed RIS-DSM scheme can deliver satisfactory error performance even in low signal-to-noise ratio environments.

Fixed-Time Sliding Mode Control With Varying Exponent Coefficient for Modular Reconfigurable Flight Arrays

The modular system can change its physical structure by self-assembly and self-disassembly between modules to dynamically adapt to task and environmental requirements. Recognizing the adaptive capability of modular systems, we introduce a modular reconfigurable flight array(MRFA) to pursue a multifunction aircraft fitting for diverse tasks and requirements,and investigate the attitude control and the control allocation problem by using the modular reconfigurable flight array as a platform. First, considering the variable and irregular topological configuration of the modular array, a center-of-mass-independent flight array dynamics model is proposed to allow control allocation under over-actuated situations. Secondly, in order to meet the stable, fast and accurate attitude tracking performance of the MRFA, a fixed-time convergent sliding mode controller with state-dependent variable exponent coefficients is proposed to ensure fast convergence rate both away from and near the system equilibrium point without encountering the singularity. It is shown that the controller also has fixed-time convergent characteristics even in the presence of external disturbances. Finally,simulation results are provided to demonstrate the effectiveness of the proposed modeling and control strategies.

Reconfigurable and polarization-dependent optical filtering for transflective full-color generation utilizing low-loss phase-change materials

All-dielectric metasurface, which features low optical absorptance and high resolution, is becoming a promising candidate for full-color generation. However, the optical response of current metamaterials is fixed and lacks active tuning. In this work, we demonstrate a reconfigurable and polarization-dependent active color generation technique by incorporating low-loss phase change materials(PCMs) and CaF_2 all-dielectric substrate. Based on the strong Mie resonance effect and low optical absorption structure, a transflective, full-color with high color purity and gamut value is achieved. The spectrum can be dynamically manipulated by changing either the polarization of incident light or the PCM state. High transmittance and reflectance can be simultaneously achieved by using low-loss PCMs and substrate. The novel active metasurfaces can bring new inspiration in the areas of optical encryption, anti-counterfeiting, and display technologies.

Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

Wideband low-scattering metasurface with an in-band reconfigurable transparent window

Active metasurfaces with dynamically reconfigurable functionalities are highly demanded in various practical applications.Here,we propose a wideband low-scattering metasurface that can realize an in-band reconfigurable transparent window by altering the operation states of the PIN diodes loaded on the structures.The metasurface is composed of a band-pass frequency selective surface(FSS)sandwiched between two polarization conversion metasurfaces(PCMs).PIN diodes are integrated into the FSS to switch the transparent window,while a checkerboard configuration is applied in PCMs for the diffusive-reflective function.A sample with 20×20 elements is designed,fabricated,and experimentally verified.Both simulated and measured results show that the in-band functions can be dynamically switched between beam-splitting scattering and high transmission by controlling the biasing states of the diodes,while low backscattering can be attained outside the passband.Furthermore,the resonant structures of FSS also play the role of feeding lines,thus significantly eliminating extra interference compared with conventional feeding networks.We envision that the proposed metasurface may provide new possibilities for the development of an intelligent stealth platform and its antenna applications.

Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

Research and design of matrix operation accelerator based on reconfigurable array

In the case of massive data,matrix operations are very computationally intensive,and the memory limitation in standalone mode leads to the system inefficiencies.At the same time,it is difficult for matrix operations to achieve flexible switching between different requirements when implemented in hardware.To address this problem,this paper proposes a matrix operation accelerator based on reconfigurable arrays in the context of the application of recommender systems(RS).Based on the reconfigurable array processor(APR-16)with reconfiguration,a parallelized design of matrix operations on processing element(PE)array is realized with flexibility.The experimental results show that,compared with the proposed central processing unit(CPU)and graphics processing unit(GPU)hybrid implementation matrix multiplication framework,the energy efficiency ratio of the accelerator proposed in this paper is improved by about 35×.Compared with blocked alternating least squares(BALS),its the energy efficiency ratio has been accelerated by about 1×,and the switching of matrix factorization(MF)schemes suitable for different sparsity can be realized.

Machine learning algorithm partially reconfigured on FPGA for an image edge detection system

Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.

Cooperative Distributed Beamforming Design for Multi-RIS Aided Cell-Free Systems

Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.

Illumination Adaptive Identification Algorithm of a Reconfigurable Modular Robot

Reconfigurable modular robots feature high mobility due to their unconstrained connection manners.Inspired by the snake multi-joint crawling principle,a chain-type reconfigurable modular robot(CRMR)is designed,which could reassemble into various configurations through the compound joint motion.Moreover,an illumination adaptive modular robot identification(IAMRI)algorithm is proposed for CRMR.At first,an adaptive threshold is applied to detect oriented FAST features in the robot image.Then,the effective detection of features in non-uniform illumination areas is achieved through an optimized quadtree decomposition method.After matching features,an improved random sample consensus algorithm is employed to eliminate the mismatched features.Finally,the reconfigurable robot module is identified effectively through the perspective transformation.Compared with ORB,MA,Y-ORB,and S-ORB algorithms,the IAMRI algorithm has an improvement of over 11.6%in feature uniformity,and 13.7%in the comprehensive indicator,respectively.The IAMRI algorithm limits the relative error within 2.5 pixels,efficiently completing the CRMR identification under complex environmental changes.

Inter-operator spectrum sharing scheme for reconfigurable system

Bargaining based mechanism for sharing spectrum between radio access networks （RANs） belonging to multioperators is studied, to improve spectrum utilization efficiency and maximize network revenue. By introducing an intelligent agent, each RAN has the ability, which includes trading information exchanging, final decision making, and so on, to trade the spectrum with other RANs. The proposed inter-operator spectrum sharing mechanism is modeled as an infinite-horizon bargaining game with incomplete information, and the resulting bargaining game has unique sequential equilibrium. Consequently, the implementation is refined based on the analysis. Simulation results show that the proposed mechanism outperforms the conventional fixed spectrum management （FSM） method in network revenue, spectrum efficiency, and call blocking rate.

Joint Beamforming Optimization for Reconfigurable Intelligent Surface-Enabled MISO-OFDM Systems

In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.

Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication Systems in Mobility Scenarios

Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of the instantaneous channel state information(CSI)in the cascaded RIS chain makes an indispensable contribution to the performance gains.However,it is quite challenging to estimate the CSI in a time-variant scenario due to the limited signal processing capability of the passive elements embedded in a RIS pannel.In this work,a channel estimation scheme for the RIS-assisted wireless communication system is proposed,which is demonstrated to perform well in a time-variant scenario.The cascaded RIS channel is modeled as a state-space model based upon the mobility situations.In addition,to fully exploit the time correlation of channel,Kalman filter is employed by taking the prior information of channels into account.Further,the optimal reflection coefficients are derived according to the minimum mean square error(MMSE)criterion.Numerical results show that the proposed methods exhibit superior performance if compared with a conventional channel estimation scheme.

Early faults prediction of running state of electromechanical systems and reconfigurable integration of series safety monitoring systems

Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of modern, high-end and key electromechanical equipment, this paper will describe the early faults prediction method for multi-type electromechanical systems, which is favorable for predicting early faults of complex electromechanical systems in non-stationary, nonlinear, variable working conditions and long-time running state; the paper shall introduce the reconfigurable integration technology of series safety monitoring systems based on which the integrated development platform of series safety monitoring systems is built. This platform can adapt to integrated R&D of series safety monitoring systems characterized by high technology, multiple species and low volume. With the help of this platform, series safety monitoring systems were developed, and the Remote Network Security Monitoring Center for Facility Groups was built. Experimental research and engineering applications show that: this new fault prediction method has realized the development trend features extraction of typical electromechanical systems, multi-information fusion, intelligent information decision-making and so on, improving the processing accuracy, relevance and applicability of information; new reconfigurable integration technologies have improved the integration level and R&D efficiency of series safety monitoring systems as well as expanded the scope of application; the series safety monitoring systems developed based on reconfigurable integration platform has already played an important role in many aspects including ensuring safety operation of equipment, stabilizing product quality, optimizing running state, saving energy consumption, reducing environmental pollution, improving working conditions, carrying out scientific maintenance, advancing equipment utilization, saving maintenance charge and enhancing the level of information management.

Configuration Selection for Reconfigurable Manufacturing Systems by Means of Characteristic State Space

The configuration selection for reconfigurable manufacturing systems（RMS） have been tackled in a number of studies by using analytical or simulation models. The simulation models are usually based on fewer assumptions than the analytical models and therefore are more wildly used in modeling complex RMS. But in the absence of an efficient gradient analysis method of the objective function, it is time-consuming in solving large-scale problems by using a simulation model coupled with a meta-heuristics algorithm. In this paper, a new approach by means of characteristic state space is presented to improve the efficiency of the configuration selection for an RMS. First, a characteristic state equation is set up to represent the input and the output resources of each basic activity in an RMS. A production process model in terms of matrix equations is established by iterating the equations of basic activities according to the resource flows. This model introduces the production process into a characteristic state space for further analysis. Second, the properties of the characteristic state space are presented. On the basis of these properties, the configuration selection in an RMS is considered as a path-planning problem, and the gradient of the objective function is computed. Modified simulated annealing（SA） is also presented, in which neighborhood generation is guided by the gradient to accelerate convergence and reduce the run time of the optimization procedure. Finally, several case studies on the configuration selection for some actual reconfigurable assembly job-shops are presented and compared to the classical SA. The comparison shows relatively positive results. This study provides a more efficient configuration selection approach by using the gradient of the objective function and presents the relevant theories on which it is based.