Research on Mixed Logic Dynamic Modeling and Finite Control Set Model Predictive Control of Multi-Inverter Parallel System

Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems.

Selective maintenance problem for series–parallel system under economic dependence

In view of the high complexity of the objective world, an economic dependence between subsystems(paired and unpaired) is proposed, and then the maintenance cost and time under different economic dependences are formulated in a simple and consistent manner. Selective maintenance problem under economic dependence(EDSMP) is presented based on a series–parallel system in this paper. A case study shows that the system reliability is promoted to a certain extent, which can validate the validity of the EDSMP model. The influence of the ratio of set-up cost on system performance is mainly discussed under different economic dependences. Several existing improvements of classical exhaust algorithm are further modified to solve a large sized EDSMP rapidly. Experimental results illustrate that these improvements can reduce CPU time significantly.Furthermore the contribution of each improvement is defined here, and then their contributions are compared thoroughly.

Robotic Intra-Operative Ultrasound:Virtual Environments and Parallel Systems

Robotic intra-operative ultrasound has the potential to improve the conventional practice of diagnosis and procedure guidance that are currently performed manually.Working towards automatic or semi-automatic ultrasound,being able to define ultrasound views and the corresponding probe poses via intelligent approaches become crucial.Based on the concept of parallel system which incorporates the ingredients of artificial systems,computational experiments,and parallel execution,this paper utilized a recent developed robotic trans-esophageal ultrasound system as the study object to explore the method for developing the corresponding virtual environments and present the potential applications of such systems.The proposed virtual system includes the use of 3 D slicer as the main workspace and graphic user interface(GUI),Matlab engine to provide robotic control algorithms and customized functions,and PLUS(Public software Library for Ultra Sound imaging research)toolkit to generate simulated ultrasound images.Detailed implementation methods were presented and the proposed features of the system were explained.Based on this virtual system,example uses and case studies were presented to demonstrate its capabilities when used together with the physical TEE robot.This includes standard view definition and customized view optimization for pre-planning and navigation,as well as robotic control algorithm evaluations to facilitate real-time automatic probe pose adjustments.To conclude,the proposed virtual system would be a powerful tool to facilitate the further developments and clinical uses of the robotic intra-operative ultrasound systems.

RELIABILITY ANALYSIS FOR A REPAIRABLE PARALLEL SYSTEM WITH TIME-VARYING FAILURE RATES

To solve a real problem:how to calculate the reliability of a system with time-varying failure rates in industry systems,this paper studies a model for the load-sharing parallel system with time-varying failure rates,and obtains calculating formulas of reliability and availability of the system by solving differential equations.In this paper,the failure rates are expressed in polynomial configuration.The constant,linear and Weibull failure rate are in their special form.The polynomial failure rates provide flexibility in modeling the practical time-varying failure rates.

Parallel programming characteristics of a DSP-based parallel system

This paper firstly introduces the structure and working principle of DSP-based parallel system, parallel accelerating board and SHARC DSP chip. Then it pays attention to investigating the system’s programming characteristics, especially the mode of communication, discussing how to design parallel algorithms and presenting a domain-decomposition-based complete multi-grid parallel algorithm with virtual boundary forecast (VBF) to solve a lot of large-scale and complicated heat problems. In the end, Mandelbrot Set and a non-linear heat transfer equation of ceramic/metal composite material are taken as examples to illustrate the implementation of the proposed algorithm. The results showed that the solutions are highly efficient and have linear speedup.

Reliability analysis of a two-dependent-unit parallel system with a standby unit

A parallel system with two active components and a cold standby unit is studied in this paper. The two simultaneously working components are dependent and the copula function is used to model their dependence. An explicit expression is obtained for the mean time to failure of the system in terms of the copula function and marginal lifetime distributions in two different cases. As an application,numerical calculations are presented corresponding to two different copula functions and marginal lifetime distributions.

Programming for scientific computing on peta-scale heterogeneous parallel systems

Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.

Improved Hungarian algorithm for assignment problems of serial-parallel systems

In order to overcome the shortcoming of the classical Hungarian algorithm that it can only solve the problems where the total cost is the sum of that of each job, an improved Hungarian algorithm is proposed and used to solve the assignment problem of serial-parallel systems. First of all, by replacing parallel jobs with virtual jobs, the proposed algorithm converts the serial-parallel system into a pure serial system, where the classical Hungarian algorithm can be used to generate a temporal assignment plan via optimization. Afterwards, the assignment plan is validated by checking whether the virtual jobs can be realized by real jobs through local searching. If the assignment plan is not valid, the converted system will be adapted by adjusting the parameters of virtual jobs, and then be optimized again. Through iterative searching, the valid optimal assignment plan can eventually be obtained.To evaluate the proposed algorithm, the valid optimal assignment plan is applied to labor allocation of a manufacturing system which is a typical serial-parallel system.

Load Dependent Series-Parallel Systems with Common Bus Performance Sharing Mechanism

A series-parallel system was proposed with common bus performance sharing in which the performance and failure rate of the element depended on the load it was carrying. In such a system,the surplus performance of a sub-system can be transmitted to other deficient sub-systems. The transmission capacity of the common bus performance sharing mechanism is a random variable. Effects of load on element performance and failure rate were considered in this paper. A reliability evaluation algorithm based on the universal generating function technique was suggested. Numerical experiments were conducted to illustrate the algorithm.

A Dynamic Job Scheduling Algorithm for Parallel System

One of the fundamental problems in parallel and distributed systems is deciding how to allocate jobs to processors. The goals of job scheduling in a parallel environment are to minimize the parallel execution time of a job and try to balance the user’s desire with the system’s desire. The users always want their jobs be completed as quickly as possible, while the system wants to service as many jobs as possible. In this paper, a dynamic job scheduling algorithm was introduced. This algorithm tries to utilize the information of a practical system to allocate the jobs more evenly. The communication time between the processor and scheduler is overlapped with the computation time of the processor. So the communication overhead can be little. The principle of scheduling the job is based on the desirability of each processor. The scheduler would not allocate a new job to a processor that is already fully utilized. The execution efficiency of the system will be increased. This algorithm also can be reused in other complex algorithms.

Reliability of a Large Series-parallel System in Variable Operating Conditions

In this paper, a semi-Markov model of system operation processes is proposed and its selected parameters are determined. A series-parallel multi-state system is considered, and its reliability and risk characteristics found. Subsequently, a joint model of system operation process and system multi-state reliability and risk is constructed. Moreover, the asymptotic approach to reliability and risk evaluation of a multi-state series-parallel system in its operation process is applied to a port grain transportation system.

On the Communication-Efficiency of Parallel Systems

This peper defines the communication-efficiency, which is directly related to the cost-efficiency, and Studies the relationship between the communication-efficiency and the processor-efficiency when they are applied to scalability analysis. An example of algorithms is given to analyze some typical architectures.

The Research on Stability of DC/DC in Parallel System

In this paper, a main structure of DC distributed power system is introduced;the stability of the output voltage in parallel system is put forward. This paper analyses the output impedance of master-slave current sharing mode and average current sharing, analyses the stability of parallel system through simulation, there is Right-half plane (RHP) polar in the Bode plot of input impedance. At last this paper distinguishes whether this system is stability and verifies the validity of the simulation.

Multilayer Hex-Cells: A New Class of Hex-Cell Interconnection Networks for Massively Parallel Systems

Scalability is an important issue in the design of interconnection networks for massively parallel systems. In this paper a scalable class of interconnection network of Hex-Cell for massively parallel systems is introduced. It is called Multilayer Hex-Cell (MLH). A node addressing scheme and routing algorithm are also presented and discussed. An interesting feature of the proposed MLH is that it maintains a constant network degree regardless of the increase in the network size degree which facilitates modularity in building blocks of scalable systems. The new addressing node scheme makes the proposed routing algorithm simple and efficient in terms of that it needs a minimum number of calculations to reach the destination node. Moreover, the diameter of the proposed MLH is less than Hex-Cell network.

Asymptotic Stability of Gaver’s Parallel System Attended by a Cold Standby Unit and a Repairman with Multiple Vacations

We investigate Gaver’s parallel system attended by a cold standby unit and a repairman with multiple vacations. By analysing the spectral distribution of the system operator and taking into account the irreducibility of the semigroup generated by the system operator we prove that the dynamic solution converges strongly to the steady state solution. Thus we obtain asymptotic stability of the dynamic solution of the system.

Well-Posedness of Gaver’s Parallel System Attended by a Cold Standby Unit and a Repairman with Multiple Vacations

We investigate Gaver’s parallel system attended by a cold standby unit and a repairman with multiple vacations. By using C0-semigroup theory of linear operators in the functional analysis, we prove well-posedness and the existence of the unique positive dynamic solution of the system.

Optimal Redundancy Allocation in Hierarchical Series-Parallel Systems Using Mixed Integer Programming

Reliability optimization plays an important role in design, operation and management of the industrial systems. System reliability can be easily enhanced by improving the reliability of unreliable components and/or by using redundant configuration with subsystems/components in parallel. Redundancy Allocation Problem (RAP) was studied in this research. A mixed integer programming model was proposed to solve the problem, which considers simultaneously two objectives under several resource constraints. The model is only for the hierarchical series-parallel systems in which the elements of any subset of subsystems or components are connected in series or parallel and constitute a larger subsystem or total system. At the end of the study, the performance of the proposed approach was evaluated by a numerical example.

Reliability Optimization of Entropy Based Series-Parallel System Using Global Criterion Method

In this paper, we have considered a series-parallel system to find out optimum system reliability with an additional entropy objective function. Maximum system reliability of series-parallel system is depending on proper allocation of redundancy component in different stage. The goal of entropy based reliability redundancy allocation problem is to find optimal number of redundancy component in each stage such a manner that maximize the system reliability subject to available total system cost. Global criterion method is used to analyze entropy based reliability optimization problem with different weight function of objective functions. Numerical examples have been provided to illustrate the model.

Reliability Measure of a Relay Parallel System under Dependence Conditions

In a relay system of dependent components, the failure to close reliability measure is given as a Girsanov transform of the failure to open reliability measure.

Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution.However,there is,currently,nearly no standard technical framework for objective and quantitative intelligence evaluation.In this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation theories.On this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment results.Experiment results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.