A reconfigurable dynamic Bayesian network for digital twin modeling of structures with multiple damage modes

Dynamic Bayesian networks(DBNs)are commonly employed for structural digital twin modeling.At present,most researches only consider single damage mode tracking.It is not sufficient for a reusable spacecraft as various damage modes may occur during its service life.A reconfigurable DBN method is proposed in this paper.The structure of the DBN can be updated dynamically to describe the interactions between different damages.Two common damages(fatigue and bolt loosening)for a spacecraft structure are considered in a numerical example.The results show that the reconfigurable DBN can accurately predict the acceleration phenomenon of crack growth caused by bolt loosening while the DBN with time-invariant structure cannot,even with enough updates.The definition of interaction coefficients makes the reconfigurable DBN easy to track multiple damages and be extended to more complex problems.The method also has a good physical interpretability as the reconfiguration of DBN corresponds to a specific mechanism.Satisfactory predictions do not require precise knowledge of reconfiguration conditions,making the method more practical.

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.

Deep reinforcement learning based multi-level dynamic reconfiguration for urban distribution network:a cloud-edge collaboration architecture

With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.

A Concept of Dynamically Reconfigurable Real-time Vision System for Autonomous Mobile Robotics

This paper describes specific constraints of vision systems that are dedicated to be embedded in mobile robots. If PC-based hardware architecture is convenient in this field because of its versatility, flexibility, performance, and cost, current real-time operating systems are not completely adapted to long processing with varying duration, and it is often necessary to oversize the system to guarantee fail-safe functioning. Also, interactions with other robotic tasks having more priority are difficult to handle. To answer this problem, we have developed a dynamically reconfigurable vision processing system, based on the innovative features of Cleopatre real-time applicative layer concerning scheduling and fault tolerance. This framework allows to define emergency and optional tasks to ensure a minimal quality of service for the other subsystems of the robot, while allowing to adapt dynamically vision processing chain to an exceptional overlasting vision process or processor overload. Thus, it allows a better cohabitation of several subsystems in a single hardware, and to develop less expensive but safe systems, as they will be designed for the regular case and not rare exceptional ones. Finally, it brings a new way to think and develop vision systems, with pairs of complementary operators.

A High-level Architecture for Intrusion Detection on Heterogeneous Wireless Sensor Networks: Hierarchical, Scalable and Dynamic Reconfigurable

Networks protection against different types of attacks is one of most important posed issue into the network and information security domains. This problem on Wireless Sensor Networks (WSNs), in attention to their special properties, has more importance. Now, there are some of proposed solutions to protect Wireless Sensor Networks (WSNs) against different types of intrusions;but no one of them has a comprehensive view to this problem and they are usually designed in single-purpose;but, the proposed design in this paper has been a comprehensive view to this issue by presenting a complete Intrusion Detection Architecture (IDA). The main contribution of this architecture is its hierarchical structure;i.e. it is designed and applicable, in one, two or three levels, consistent to the application domain and its required security level. Focus of this paper is on the clustering WSNs, designing and deploying Sensor-based Intrusion Detection System (SIDS) on sensor nodes, Cluster-based Intrusion Detection System (CIDS) on cluster-heads and Wireless Sensor Network wide level Intrusion Detection System (WSNIDS) on the central server. Suppositions of the WSN and Intrusion Detection Architecture (IDA) are: static and heterogeneous network, hierarchical, distributed and clustering structure along with clusters' overlapping. Finally, this paper has been designed a questionnaire to verify the proposed idea;then it analyzed and evaluated the acquired results from the questionnaires.

Component Based Dynamic Reconfigurable Test System

In this paper,a novel component based framework of test system is presented for the new requirements of dynamic changes of test functions and reconfiguration of test resources.The complexity of dynamic reconfiguration arises from the scale, redirection,extensibility and interconnection of components in test system.The paper is started by discussing the component assem- bly based framework which provide the open platform to the deploy of companents and then the script interpreter model is introduced to dynamically create the components and build the test system by analyzing XML based information of test system.A pipeline mod- el is presented to provide the data channels and behavior reflection among the components.Finally,a dynamic reconfigurable test system is implemented on the basis of COM and applied in the remote test and control system of CNC machine.

Dynamically Reconfigurable Encryption System of the AES

Reconfigurable computing has grown to become an important and large field of research, it offers advantages over traditional hardware and software implementations of computational algorithms. The Advanced Encryption Standard （AES） algorithm is widely applied in government department and commerce. This paper analyzed the AES algorithms with different cipher keys, adopted a novel key scheduler that generated the round key real-time, proposed a dynamically reconfigurable encryption system which supported the AES algorithm with different cipher keys, and designed the architecture of the reconfigurable system. The dynamically reconfigurable AES system had been realized on FPGA. The result proves that the reconfigurable AES system is flexible, lower cost and high security level.

A Low-Area, Low-Power Dynamically Reconfigurable 64-Bit Media Signal Processing Adder

Multimedia devices like cellphones, radios, televisions, and computers require low-area and energy-efficient dynamically reconfigurable data paths to process the greedy computation algorithms for real-time audio/video signal and image processing. In this paper, a novel low-area, energy-efficient 64-bit dynamically reconfigurable adder is presented. This adder can be run-time configured to different reconfigurable word lengths based on the partition signal commands provided. Moreover, the design is partitioned into sub-blocks based on functionality to save power, i.e., configuring the computation only for the necessary data path, thus avoiding the unnecessary switching power from the data path computed values that do not get used. Only functions that are needed are powered on, and the rest of the functionality is powered off. The proposed 64-bit dynamically reconfigurable media signal processing (MSP) adder is implemented in the 180 nm CMOS technology at 1.8 V, requiring an area of 39,478 μm2 and a power of 79.24 mW. The dynamic MSP adder achieves a 15.7% reduction in area and a 59.2% reduction in power than the 64-bit MSP adder.

Dynamic Reconfigurable Structure with Rate Distortion Optimization

The Rate Distortion Optimization(RDO)algorithm in High Efficiency Video Coding(HEVC)has many iterations and a large number of calculations.In order to decrease the calculation time and meet the requirements of fast switching of RDO algorithms of different scales,an RDO dynamic reconfigurable structure is proposed.First,the Quantization Parameter(QP)and bit rate values were loaded through an H⁃tree Configurable Network(HCN),and the execution status of the array was detected in real time.When the switching request of the RDO algorithm was detected,the corresponding configuration information was delivered.This self⁃reconfiguration implementation method improved the flexibility and utilization of hardware.Experimental results show that when the control bit width was only increased by 31.25%,the designed configuration network could increase the number of controllable processing units by 32 times,and the execution cycle was 50%lower than the same type of design.Compared with previous RDO algorithm,the RDO algorithm implemented on the reconfigurable array based on the configuration network had an average operating frequency increase of 12.5%and an area reduction of 56.4%.

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.

Dynamic behavior of tunneling triboelectric charges in two-dimensional materials

Although the research history of triboelectrification has been more than 2000 years, there are still many problems to be solved so far.The use of scanning probe microscopy provides an important way to quantitatively study the transfer, accumulation, and dissipation of triboelectric charges in the process of triboelectrification. Two-dimensional materials are considered to be key materials for new electronic devices in the post-Moore era due to their atomic-scale size advantages. If the electrostatic field generated by triboelectrification can be used to replace the traditional gate electrostatic field, it is expected to simplify the structure of two-dimensional electronic devices and reconfigure them at any time according to actual needs. Here, we investigate the triboelectrification process of various two-dimensional materials such as MoS_(2), WSe_(2),and ZnO. Different from traditional bulk materials, after two-dimensional materials are rubbed, the triboelectric charges generated may tunnel through the two-dimensional materials to the underlying substrate surface. Because the tunneling triboelectric charge is protected by the twodimensional material, its stable residence time on the substrate surface can reach more than 7 days, which is more than tens of minutes for the traditional triboelectric charge. In addition, the electrostatic field generated by the tunneling triboelectric charge can effectively regulate the carrier transport performance of two-dimensional materials, and the source–drain current of the field effect device regulated by the triboelectric floating gate is increased by nearly 60 times. The triboelectric charge tunneling phenomenon in two-dimensional materials is expected to be applied in the fields of new two-dimensional electronic devices and reconfigurable functional circuits.

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.

Application of Global Dynamic Reconfiguration in Artificial Neural Network System based on Field Programmable Gate Array

Presented is a global dynamic reconfiguration design of an artificial neural network based on field programmable gate array(FPGA). Discussed are the dynamic reconfiguration principles and methods. Proposed is a global dynamic reconfiguration scheme using Xilinx FPGA and platform flash. Using the revision capabilities of Xilinx XCF32P platform flash, an artificial neural network based on Xilinx XC2V30P Virtex-Ⅱ can be reconfigured dynamically from back propagation(BP) learning algorithms to BP network testing algorithms. The experimental results indicate that the scheme is feasible, and that, using dynamic reconfiguration technology, FPGA resource utilization can be reduced remarkably.

FSM deconposition VLSI architecture for dynamically reconfiguration

While some applications in memory can be constrained by memory bandwidth and memory cost, this paper proposes a transformation of the application into a one-bit FSM. When the finite state machine is very large, one way to improve the area and delay efficiently is to break down the large finite state machine into many smaller machines. The area efficiency can be improved if fewer machines are active simultaneously in the pipelined architecture. This can be achieved when using dynamic reconfiguration to map several sub machines onto the same hardware. This paper presents a methodology to break down the large finite state machine into many smaller machines and an architecture for the dynamically reconfiguration.

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.

Application of Remote FPGA Dynamic Reconfiguration System in LED Lighting

The dynamic reconfiguration technique based on field-programmable gate array （FPGA） can improve the resource utilization. Discussed are the dynamic reconfiguration principles and methods. Proposed is a remote dynamic reconfiguration scheme using Xilinx Virtex-Ⅱ FPGA and SMCS Ethernet Physical layer transceiver（PHY）. The hardware of the system is designed with Xilinx Virtex-U XC2V30P FPGA that embedds MicroBlaze and MAC IP core, and its network communication software based on transmission control protoeol/Internet protocol （TCP/IP） protocol is programmed by loading LwIP to MicroBlaze. The experimental results indicate that the remote FPGA dynamic reconfiguration system（RFDRS） can switch freely in the eight lighting modes of light emitting diodes （LED）, and that, using dynamic reconfiguration technology, FPGA resource utilization can be reduced remarkably, which is advantageous in the system upgrade and software update.

Dynamic Load Balancing with Overlay-Based Reconfiguration for Wireless Sensor Networks

Wireless sensor networks are characterized by multihop wireless links and resource constrained nodes. In terms of data collection and forwarding scheduling, this paper investigates the load balancing in sensor nodes and wireless link based on the performance of wireless sensor networks. Leveraging the property of dissimilarity distribution, a method to quantitatively evaluate the benefits of load balancing is presented, in order to access the profitability. Then a novel Dynamic Load Balancing of Overlay-based WSN (DLBO) algorithm has been put forward. In particular, the tradeoff between transferring ratio and the load imbalance among nodes is discussed. The load balancing method in this paper outperforms others based on balancing factor, different nodes number and data scales of applications. The proposed model and analytical results can be effectively applied for reliability analysis for other wireless applications (e.g., persistent data delivery is involved).

Research on the Structural Rigidity Characteristics of a Reconfigurable TBM Thrust Mechanism

To improve the adaptability of TBMs in diverse geological environments,this paper proposes a reconfigurable Type-V thrust mechanism(V-TM)with rearrangeable working states,in which structural stiffness can be automatically altered during operation.Therefore,millions of configurations can be obtained,and thousands of instances of working status per configuration can be set respectively.Nonetheless,the complexity of configurations and diversity of working states contributes to further complications for the structural stiffness algorithm.This results in challenges such as difficulty calculating the payload compliance index and the environment adaptability index.To solve this problem,we use the configuration matrix to describe the relationship between propelling jacks under reconfiguration and adopt pattern vectors to describe the working state of each hydraulic cylinder.Then,both the dynamic compatible equation between propeller forces of the hydraulic cylinders and driving forces,and the kinematic harmonizing equation between the hydraulic cylinder displacements and their deformations are established.Next,we derive the stiffness analytical equation using Hooke’s law and the Jacobian Matrix.The proposed approach provides an effective algorithm to support structural rigidity analysis,and lays a solid theoretical foundation for calculating the performance indexes of the V-TM.We then analyze the rigidity characteristics of typical configurations under different working states,and obtain the main factors affecting structural stiffness of the V-TM.The results show the deviation degree of structural parameters in hydraulic cylinders within the same group,and the working status of propelling jacks.Finally,our constructive conclusions contribute valuable information for matching and optimization by drawing on the factors that affect the structural rigidity of the V-TM.

Survey on nonlinear reconfigurable flight control

An overview on nonlinear reconfigurable flight control approaches that have been demonstrated in flight-test or highfidelity simulation is presented. Various approaches for reconfigurable flight control systems are considered, including nonlinear dynamic inversion, parameter identification and neural network technologies, backstepping and model predictive control approaches. The recent research work, flight tests, and potential strength and weakness of each approach are discussed objectively in order to give readers and researchers some reference. Finally, possible future directions and open problems in this area are addressed.

A Survey of Control Structures for Reconfigurable Petri Nets

Software systems are increasingly executed in dynamic infrastructures. These infrastructures are dynamic as they are themselves subject to change as they support various applications that may or may not share some of the resources. Dynamic software systems become more and more important, but are difficult to handle. Modeling and simulating dynamic systems requires the representation of their processes and the system changes within one model. To that effect, reconfigurable Petri nets consist of a Petri net and a set of rules that can modify the Petri net. Their main feature is the capability to model complex coordination behavior in dynamically adapting infrastructures. The interplay of both levels of dynamic behavior requires a very precise description, so the specification when and which rules are to be applied plays a crucial role for the convenient use of reconfigurable nets. We differentiate several types of reconfigurable Petri nets and present a survey of control structure for these types, reconfigurable Petri nets. These control structures either concern the infrastructure, i.e., the rules and transformations or the system part, i.e., the firing behavior, or both. They are introduced by a short characterization and illustrated by examples. We state the results for various Petri net types and the tools supporting the different control structures.