COMPENSATION CONTROL OF REAL-TIME UNBALANCE FORCE FOR ACTIVE MAGNETIC BEARING SYSTEM

Aiming at the stability and others properties of active magnetic bearing （AMB） system influenced by the periodic unbalance stimulation synchronous with rotor rotational speed, a new real-time adaptive feed-forward unbalance force compensation scheme is proposed based on variable step-size least mean square（LMS） algorithm as the feed-forward compensation controller. The controller can provide some suitable sinusoidal signals to com- pensate the feedback unbalance response signals synchronous with the rotary frequency, then reduce the fluctua- tion of the control currents and weaken the active control of AMB system. The variable step-size proportional to the rotational frequency is deduced by analyzing the principle of normal LMS algorithm and its deficiency in the application of real-time filtering of AMB system. Experimental results show that the new method can implement real-time unbalance force compensation in a wide frequency band, reduce the effect of unbalance stimulant force on the housing of AMB system, and provide convenience to improve rotational speed.

A sensor transaction scheduling algorithm for maintaining real-time data temporal validity

A new scheduling algorithm called deferrable scheduling with time slice exchange (DS-EXC) was proposed to maintain the temporal validity of real-time data. In DS-EXC, the time slice exchange method was designed to further defer the release time of transaction instances derived by the deferrable scheduling algorithm (DS-FP). In this way, more CPU time would be left for lower priority transactions and other transactions. In order to minimize the scheduling overhead, an off-line scheme was designed. In particular, the schedule for a transaction set is generated off-line until a repeating pattern is found, and then the pattern is used to construct the schedule on-line. The performance of DS-EXC was evaluated by sets of experiments. The results show that DS-EXC outperforms DS-FP in terms of increasing schedulable ratio. It also provides better performance under mixed workloads.

Real-time Design Constraints in Implementing Active Vibration Control Algorithms

Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control （AVC） algorithm for a flexible beam system simulated using the finite difference （FD） method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.

Real-Time Method for Detecting Harmonic and Reactive Currents of Single-Phase Circuits

According to the characteristics of single-phase circuits and demand of using active filter for real-time detecting harmonic and reactive currents, a detecting method based on Fryze＇s power definition is proposed. The results of theoretical analysis and simula- tion show that the proposed method is effective in realtime detecting of instantaneous harmonic and reactive currents in single-phase circuits. When only detecting the total reactive currents, this method does not need a phase-locked loop circuit, and it also can be used in some special applications to provide different compensations on the ground of different requirements of electric network. Compared with the other methods based on the theory of instantaneous reactive power, this method is simple and easy to realize.

Blockchain-Based Power Transaction Method for Active Distribution Network

A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.

Efficacy of Real-Time Transaction Processing System

Real-Time Transaction Processing System(RTTPS)is a type of e-government that processes documents using electronic communication technology.In this time of the pandemic,the study contributes to the necessity to perform more processing online and less face-to-face.In terms of retrieving information,a comparison between Porter’s Stemming algorithm and this study was performed.The study aims to design a database that will serve as a repository of information in retrieving information and also to examine the efficacy of the real-time process in securing the government requirements using the Technology Acceptance Model.The respondents of this study have perceived ease of use and usefulness on the impact when securing the community tax certificate.

Real-Time Detection of Unstable Control Loop Behavior in a Feedback Active Noise Cancellation System for In-Ear Headphones

Active noise controls are used in a wide field of applications to cancel out unwanted surrounding noise. Control systems based on the feedback structure however have the disadvantage that they may become unstable during run-time due to changes in the control path—in this context including the listener’s ear. Especially when applied to active noise cancellation (ANC) headphones, the risk of instability is associated with the risk of harmful influence on the listener’s ear, which is exposed to the speaker in striking distance. This paper discusses several methods to enable the analysis of a feedback ANC system during run-time to immediately detect instability. Finally, a solution is proposed, which identifies the open loop behavior parametrically by means of an adaptive filter to subsequently evaluate the coefficients regarding stability.

Intercross real-time control strategy in alternating activated sludge process for short-cut biological nitrogen removal treating domestic wastewater

To develop technically feasible and economically favorable dynamic process control(DPC)strategies for an alternating activated sludge(AAS)system,a bench-scale continuous-flow alternating aerobic and anoxic reactor,performing short-cut nitrogen removal from real domestic wastewater was operated under different control strategies for more than five months.A fixed-time control(FTC) study showed that bending-points on pH and oxidation-reduction potential(ORP)profiles accurately coincided with the major biologic...

Active X数据对象之事务控制在VB和DELPHI中的应用

事务控制是数据库应用系统中的关键技术之一 ,本文先对事务控制的概念以及微软的ActiveX数据对象 (ADO)的事务控制做了简介 ,之后以一个具体的实例给出ActiveX数据对象的事务控制在VB和DELPHI中的使用方法。

Safety-assured,real-time neural active fault management for resilient microgrids integration

Federated-learning-based active fault management(AFM)is devised to achieve real-time safety assurance for microgrids and the main grid during faults.AFM was originally formulated as a distributed optimization problem.Here,federated learning is used to train each microgrid’s network with training data achieved from distributed optimization.The main contribution of this work is to replace the optimization-based AFM control algorithm with a learning-based AFM control algorithm.The replacement transfers computation from online to offline.With this replacement,the control algorithm can meet real-time requirements for a system with dozens of microgrids.By contrast,distributed-optimization-based fault management can output reference values fast enough for a system with several microgrids.More microgrids,however,lead to more computation time with optimization-based method.Distributed-optimization-based fault management would fail real-time requirements for a system with dozens of microgrids.Controller hardware-in-the-loop real-time simulations demonstrate that learning-based AFM can output reference values within 10 ms irrespective of the number of microgrids.

Applying real-time control to enhance the performance of nitrogen removal in CAST system

A bench-scale reactor（72 L） red with domestic sewage, was operated more than 3 months with three operation modes： traditional mode, modified mode and real-time control mode, so as to evaluate effects of the operation mode on the system performance and to develop a feasible control strategy. Results obtained from fixed-time control study indicate that the variations of the pH and oxidation-reduction potential（ORP） profiles can represent dynamic characteristics of system and the cycle sequences can be controlled and optimized by the control points on the pH and ORP profiles. A control strategy was, therefore, developed and applied to real-time control mode. Compared with traditional mode, the total nitrogen（TN） removal can be increased by approximately 16% in modified mode and a mean TN removal of 92% was achieved in real-time control mode. Moreover, approximately 12.5% aeration energy was saved in real- time control mode. The result of this study shows that the performance of nitrogen removal was enhanced in modified operation mode. Moreover, the real-time control made it possible to optimize process operation and save aeration energy.

Validation concurrency control protocol in parallel real-time database systems

In parallel real-time database systems, concurrency control protocols must satisfy time constraints as well as the integrity constraints. The authors present a validation concurrency control(VCC) protocol, which can enhance the performance of real-time concurrency control mechanism by reducing the number of transactions that might miss their deadlines, and compare the performance of validation concurrency control protocol with that of HP2PL(High priority two phase locking) protocol and OCC-TI-WAIT-50(Optimistic concurrency control-time interval-wait-50) protocol under shared-disk architecture by simulation. The simulation results reveal that the protocol the author presented can effectively reduce the number of transactions restarting which might miss their deadlines and performs better than HP2PL and OCC-TI-WAIT-50. It works well when arrival rate of transaction is lesser than threshold. However, due to resource contention the percentage of missing deadline increases sharply when arrival rate is greater than the threshold.

Active并发控制—分布事务管理的目标统一

本文综述了当前分布式数据库(DDB)并发控制研究状况。提出了一种比较接近真实的DDBMS参考模型,在此基础上对典型的分布并发控制策略作出正确的集成。最后给出了Active并发控制的实现方案。

Schedulability analysis for linear transactions under fixed priority hybrid scheduling

In hard real-time systems, schedulability analysis is not only one of the important means of guaranteeing the timelines of embedded software but also one of the fundamental theories of applying other new techniques, such as energy savings and fault tolerance. However, most of the existing schedulability analysis methods assume that schedulers use preemptive scheduling or non-preemptive scheduling. In this paper, we present a schedulability analysis method, i.e., the worst-case hybrid scheduling (WCHS) algorithm, which considers the influence of release jitters of transactions and extends schedulability analysis theory to timing analysis of linear transactions under fixed priority hybrid scheduling. To the best of our knowledge, this method is the first one on timing analysis of linear transactions under hybrid scheduling. An example is employed to demonstrate the use of this method. Experiments show that this method has lower computational complexity while keeping correctness, and that hybrid scheduling has little influence on the average worst-case response time (WCRT), but a negative impact on the schedulability of systems.

Simulation research of discrete sliding mode control for active power filter

Because of the widely-used nonlinear loads, the problems of harmonics and low power factor in power systems are becoming more and more serious. In view of the above problems, a shunt three-phase active power filter （SAPF） based on discrete sliding mode control to suppress the harmonics was designed and the power factor improved. First, built the mathematical model of SAPF. Then, controlled the switch through analyzing the harmonic current that was controlled signal using discrete sliding mode control. Through simulation using MATLAB, verified the validity of the algorithm. By the simulation waveforms, it can be found that after the load current containing a large number of harmonics passes the active power filter, the waveform of the power current approximately becomes a sine wave and the harmonics is significantly reduced. As a result, it plays a good role in purifying power systems. Moreover, from the waveforms of harmonic current and power current, it can be found that the algorithm has a faster tracking speed. The waveform can fect.

Real-time Operation Optimization in Active Distribution Networks Based on Multi-agent Deep Reinforcement Learning

The increasing integration of intermittent renewable energy sources(RESs)poses great challenges to active distribution networks(ADNs),such as frequent voltage fluctuations.This paper proposes a novel ADN strategy based on multiagent deep reinforcement learning(MADRL),which harnesses the regulating function of switch state transitions for the realtime voltage regulation and loss minimization.After deploying the calculated optimal switch topologies,the distribution network operator will dynamically adjust the distributed energy resources(DERs)to enhance the operation performance of ADNs based on the policies trained by the MADRL algorithm.Owing to the model-free characteristics and the generalization of deep reinforcement learning,the proposed strategy can still achieve optimization objectives even when applied to similar but unseen environments.Additionally,integrating parameter sharing(PS)and prioritized experience replay(PER)mechanisms substantially improves the strategic performance and scalability.This framework has been tested on modified IEEE 33-bus,IEEE 118-bus,and three-phase unbalanced 123-bus systems.The results demonstrate the significant real-time regulation capabilities of the proposed strategy.

基于Activiti的考勤工作流系统设计与实现

针对大学考勤工作过程管理自动化、智能化和整合的需求,设计实现了基于Activiti的考勤工作流系统。以服务对象为中心梳理出系统核心业务,并使用Activiti Modeler完成了业务建模。介绍了系统的数据通信模式和控制数据、相关数据和应用数据的分类及作用。通过Java示例代码描述了Activiti流程部署与启动执行的步骤,并给出了基于事务内存的异常处理模式。该系统将考勤业务梳理后制定成业务流程规范,为校园信息化建设提供一定的参考。

基于Activity Service的事务性Web的研究

当前Internet的发展趋势是事务性Web,这需要解决相关的Web服务的事务性语义问题,以保证Web服务整个处理流程的完整性和可靠性。传统的事务模型以及分布式对象事务系统不再适用于新的Web环境下的需求。在总结相关工作的基础上,本文提出利用LRUOW HLS模型以及扩展WSDL规范以实现并声明事务性Web服务;并研究了扩展AS基础系统结构以解决集成Web服务的事务性的可能性。

Antiviral Activity of Recombinant Cyanovirin-N against HSV-1

In this study,a standard strain of HSV-1 (strain SM44) was used to investigate the antiviral activity of the recombinant Cyanovirin-N (CV-N) against Herpes simplex virus type 1 (HSV-1) in vitro and in vivo.Cytopathic effect (CPE) and MTT assays were used to evaluate the effect of CV-N on HSV-1 in Vero cells.The number of copies of HSV-DNA was detected by real-time fluorescence quantitative PCR (FQ-PCR).The results showed that CV-N had a low cytotoxicity on Vero cells with a CC50 of 359.03±0.56 μg/mL,and that it could not directly inactivate HSV-1 infectivity.CV-N not only reduced the CPE of HSV-1 when added before or after viral infection,with a 50% inhibitory concentration (IC50) with 2.26 and 30.16μg/mL respectively,but it also decreased the copies of HSV-1 DNA in infected host cells.The encephalitis model for HSV-1 infection was conducted in Kunming mice,and treated with three dosages of CV-N (0.5,5 & 10 mg/kg) which was administered intraperitoneally at 2h,3d,5d,7d post infection.The duration for the appearance of symptoms of encephalitis and the survival days were recorded and brain tissue samples were obtained for pathological examination (HE staining).Compared with the untreated control group,in the 5mg/kg CV-N and 10mg/kg CV-N treated groups,the mice suffered light symptoms and the number of survival days were more than 9d and 14d respectively.HE staining also showed that in 5mg/kg CV-N and 10mg/kg CV-N treated groups,the brain cells did not show visible changes,except for a slight inflammation.Our results demonstrated that CV-N has pronounced antiviral activity against HSV-1 both in vitro and in vivo,and it would be a promising new candidate for anti-HSV therapeutics.

The Relationship Between Pre-listening Activities and Listening Strategies Use

Listening strategy use is recognized as one key factor influencing English listening comprehension.The study involves three listening texts with three kinds of different pre-listening activities,namely,a copy of related Key words;a related reading passage;an easier listening preview.And the study found out four listening strategies seemed to be specially affected by the prelistening activities,elaboration,fixation,directed attention and real-time assessment of input,and effective listeners’almost used two times of metacognitive strategies than that of less-effective listeners.