New dynamic fuzzy structure and dynamic system identification

In this study, a new fuzzy system structure that reduces the number of inputs is proposed for dynamic system identification applications. Algebraic fuzzy systems have some disadvantages due to many inputs. As the number of inputs increase, the number of parameters in the training process increase and hence the classical fuzzy system becomes more complex. In the conventional fuzzy system structure, the past information of both inputs and outputs are also regarded as inputs for dynamic systems, therefore the number of inputs may not be manageable even for single input and single output systems. The new dynamic fuzzy system module (DFM) proposed here has only a single input and a single output. We have carried out identification simulations to test the proposed approach and shown that the DFM can successfully identify non-linear dynamic systems and it performs better than the classical fuzzy system.     

Linear periodic controller design for decentralized control systems

In the decentralized control of linear time-invariant (LTI) systems, a decentralized fixed mode (DFM) is a system mode which is immoveable using an LTI controller, while a quotient DFM (QDFM) is one which is immoveable using any form of nonlinear time-varying compensation. If a system has no unstable DFMs, there are well-known procedures for designing an LTI stabilizing controller; for systems which have unstable DFMs but no unstable QDFMs, we provide a simple design algorithm which yields a linear periodic sampled-data stabilizing controller.     

A branch-and-bound approach to the optimization of redundant software under failure correlation

A technique for computing optimal redundancy levels for the components of a fault-tolerant system with dependently failing redundant module versions is presented. Optimization is done under a given budget constraint and with the overall reliability as the objective. Within each component, price and estimated reliability of each redundant version is assumed to be constant. For solving the optimization problem, a branch-and-bound technique, using the solutions of continuous problem relaxations for the determination of bounds, is developed. Computational experiments with randomly generated test instances show that the suggested algorithm still performs well in situations where a computation based on dynamic programming is not feasible anymore.Scope and purposeUsing redundant program versions and thereby increasing the system reliability is a well-established way to build fault-tolerant software systems, as they are required in safety-critical computing (flight control, power plants, medical technique, defense systems). Given a certain budget for software development or purchase of software components, it makes sense to ask how this budget can be spent in order to maximize the achieved reliability. A problem occurring in this context is that different versions of a program, even if they have been developed independently from each other, do not fail independently. Our approach takes this correlation between failures into account and allows an efficient computation of optimal redundancy levels for problem instance sizes of practical interest.     

一种基于UML用例模型的软件可靠性分配方法

基于统一建模语言(UML)用例模型描述软件系统需求方面的特点;提出了以UML用例图中所包含的各个用例的使用频率作为衡量该用例的重要程度的依据,从而确定每个用例的重要度的权重因子。根据每个用例的权重因子来确定每个用例该承担的可靠性指标任务,实现软件可靠性指标在各个用例之间进行合理的分配。这种分配方案对保证软件系统的可靠性目标具有重大的现实意义,为软件后续开发、测试、维护提供可以参考的依据。     

Scenario-based run-time adaptive MPSoC systems

The ever-increasing performance demand of modern embedded applications drives the development of multi-processor system-on-chip (MPSoC) systems in the embedded domain. Today’s MPSoC-based products increasingly have to deal with multiple application execution scenarios which may change dynamically at run time. To improve the system performance, a state-of-the-art solution is to dynamically adapting the allocation of system resources at run time for each execution scenario based on pre-determined resource schemes that have been optimized at design time. However, such approaches will not work well for MPSoC systems that have a large number of execution scenarios and/or frequent run-time variations in execution scenario behavior. In this work, we therefore propose a scalable run-time self-adaptive framework for MPSoC systems that addresses these problems, thereby considerably improving the system efficiency.     

Algebraic properties of singular systems subject to decentralized output feedback

This paper investigates algebraic properties of decentralized singular systems (DSSs) under local static output feedback. New concepts of the geometric multiplicity (GM) of the finite decentralized fixed mode (DFM), the decentralized output feedback variable polynomial (DVP), and the finite decentralized output feedback cycle index (DCI) of the DSS are defined. The formulas for determining the GM and the DCI are given in terms of the DFM and the system matrices. It is shown that almost any decentralized output feedback can make the zeros of the DVP (i.e., the closed-loop poles that are variable) distinct and away from any given finite set in the complex plane. It is also shown that the finite DFM of the DSS are those uncontrollable and/or observable finite modes of the closed-loop DSS through any single channel. Finally, the minimal number of the inputs and outputs that guarantee the finite modes of the closed-loop DSS controllable and observable is shown to be the finite DCI of the DSS. An illustrative example is provided.     

Automating manufacturability evaluation in CAD systems through expert systems approaches

Design for Manufacturability (DFM) represents a new awareness of the importance of product design as an integral part of manufacturing activities. Good design guidelines exist in industry for frequently used manufacturing processes. These guidelines are systematic statements of good design practices, empirically derived over years of design and manufacturing experience. Ensuring that the given product design conforms to each of the guidelines specific to the selected process results in better manufacturability. To meet the objectives of the DFM approach, design and manufacturing planning activities have to be combined into a single engineering effort and applied througout the life cycle of a product. Computer-aided design (CAD) systems offer powerful features such as the ability to develop complex solid models and perform engineering analyses, including stress analysis, interobject interference, collision detection, and inertial analysis. However, a prominent limitation faced by designers in CAD systems is the lack of “intelligence.” Though designs could be developed, analyzed, and perfected from a functional viewpoint in CAD systems, manufacturability consideration may get little or no attention at all. As a result, product designs that are functionally sound may be developed at a high manufacturing cost. Thus, intelligence should be incorporated in CAD systems, whereby product designs could not only be developed and analyzed but also evaluated for cost and manufacturability. This study attempts to perform this task automatically in a CAD system using a knowledge-based approach: the manufacturability criteria are considered for milling and drilling operations performed on a computerized numerically controlled (CNC) milling machine. The results obtained from the application of the expert system suggest that the expert systems methodology is a feasible method for implementing manufacturability evaluation capability in CAD systems.     

The automatic generation of load test suites and the assessment ofthe resulting software

Three automatic test case generation algorithms intended to test the resource allocation mechanisms of telecommunications software systems are introduced. Although these techniques were specifically designed for testing telecommunications software, they can be used to generate test cases for any software system that is modelable by a Markov chain provided operational profile data can either be collected or estimated. These algorithms have been used successfully to perform load testing for several real industrial software systems. Experience generating test suites for five such systems is presented. Early experience with the algorithms indicate that they are highly effective at detecting subtle faults that would have been likely to be missed if load testing had been done in the more traditional way, using hand-crafted test cases. A domain-based reliability measure is applied to systems after the load testing algorithms have been used to generate test data. Data are presented for the same five industrial telecommunications systems in order to track the reliability as a function of the degree of system degradation experienced     

Confidence-based reliability assessment considering limited numbers of both input and output test data

Simulation-based methods can be used for accurate uncertainty quantification and prediction of the reliability of a physical system under the following assumptions: (1) accurate input distribution models and (2) accurate simulation models (including accurate surrogate models if utilized). However, in practical engineering applications, often only limited numbers of input test data are available for modeling input distribution models. Thus, estimated input distribution models are uncertain. In addition, the simulation model could be biased due to assumptions and idealizations used in the modeling process. Furthermore, only a limited number of physical output test data is available in the practical engineering applications. As a result, target output distributions, against which the simulation model can be validated, are uncertain and the corresponding reliabilities become uncertain as well. To assess the conservative reliability of the product properly under the uncertainties due to limited numbers of both input and output test data and a biased simulation model, a confidence-based reliability assessment method is developed in this paper. In the developed method, a hierarchical Bayesian model is formulated to obtain the uncertainty distribution of reliability. Then, we can specify a target confidence level. The reliability value at the target confidence level using the uncertainty distribution of reliability is the confidence-based reliability, which is the confidence-based estimation of the true reliability. It has been numerically demonstrated that the proposed method can predict the reliability of a physical system that satisfies the user-specified target confidence level, using limited numbers of input and output test data.     

A knowledge-based approach to design for manufacturability

In the light of growing global competition, organizations around the world today are constantly under pressure to produce high-quality products at an economical price. The integration of design and manufacturing activities into one common engineering effort has been recognized as a key strategy for survival and growth. Design for manufacturability (DFM) is an approach to design that fosters the simultaneous involvement of product design and process design. The implementation of the DFM approach requires the collaboration of both the design and manufacturing functions within an organization. Many reasons can be cited for the inability to implement the DFM approach effectively, including: lack of interdisciplinary expertise of designers; inflexibility in organizational structure, which hinders interaction between design and manufacturing functions; lack of manufacturing cost information at the design phase; and absence of integrated engineering effort intended to maximize functional and manufacturability objectives. The purpose of this research is to show how expert systems methodology could be used to provide manufacturability expertise during the design phase of a product. An object- and rule-based expert system has been developed that has the capability: (1) to make process selection decisions based on a set of design and production parameters to achieve cost-effective manufacture; and (2) to estimate manufacturing cost based on the identified processes. The expertise for primary process selection is developed for casting and forging processes. The specialized processes considered are die casting, investment casting, sand casting, precision forging, open die forging and conventional die forging. The processes considered for secondary process selection are end milling and drilling. The cost estimation expertise is developed for the die casting process, the milling and drilling operations, and the manual assembly operations. The results obtained from the application of the expert system suggest that the use of expert systems methodology is a feasible method for implementing the DFM approach.     

Correcting geometric deviations of CNC Machine-Tools: An approach with Artificial Neural Networks

This paper presents an experimental methodology of Design for Manufacturing (DFM) used for survey and analysis of geometric deviations of CNC Machine-Tools, through their final product. These deviations generate direct costs that can be avoided through the use of Intelligent Manufacturing Systems (IMS), by the application of Artificial Neural Networks (ANNs) to predict the fabrication parameters. Finally, after the experiments, it was possible to evaluate the experimental methodology used, the equations, the variables of data adjustment and thus enable the validation of the methodology used as a tool for DFM with high potential return on product quality, development time and reliability of the process with wide application in various CNC Machines.     

Virtual Battery: A testing tool for power-aware software

Virtualization is an inexpensive and convenient method for setting up software test environments. Thus it is being widely used as a test tool for software products requiring high reliability such as mission critical cyber-physical systems. However, existing virtualization platforms do not fully virtualize the battery subsystem. Therefore, it is difficult to test battery-related features of guest systems. In this paper, we propose Virtual Battery, a battery virtualization scheme for type II full virtualization platforms. Virtual Battery takes the form of an ACPI-compatible battery device driver dedicated to each virtual machine, which virtualizes a target system. Through Virtual Battery, developers can easily manipulate the charging and battery status of each virtual machine (VM), regardless of the existence or current status of the host system’s battery. In addition, Virtual Battery emulates the behavior of batteries by discharging the virtual batteries according to the resource usages of their VMs. This feature enables VMs to act as battery resource containers. Three case studies demonstrate the effectiveness of the proposed scheme.     

On the quantitative characterization of approximate decentralized fixed modes using transmission zeros

The spectrum of a linear time-invariant multivariable system, using decentralized linear time-invariant controllers, can only be assigned to a symmetric set of complex numbers that include the decentralized fixed modes (DFM). Hence only systems with stable DFM can be stabilized. Although the concept of DFM characterizes when a decentralized controller can stabilize a system, it gives no indication of howhard it is to effect such a stabilization. A system is considered hard to stabilize if large controller gains are required. Modes that are hard to shift are termedapproximate decentralized fixed modes. In this paper two new assignability measures which quantify the difficulty of shifting a mode are derived. The first is coordinate invariant and is based on the distance between a mode and a set of transmission zeros. The second is coordinate dependent and is based on the minimum singular value of a set of transmission zero matrices. This work has been supported by the Natural Sciences are Engineering Research Council of Canada under Grant No. A4396.     

A new coherent integration method for weak maneuvering target with jerk motion

In radar systems, prolonging the integration time helps to improve the detection and estimation performance of weak target. However, in a long integration time, target's high-order motion is non-ignorable, which causes high-order range migration (RM) and Doppler frequency migration (DFM) problems. The RM and DFM defocus the integration result and lead to detection and estimation performance loss. In this paper, a new coherent integration method is proposed for maneuvering radar target with jerk motion. First, we define a new cross correlation function basing on non-uniformly resampling technique. By using this function, we eliminate the range migration (RM) and Doppler frequency migration (DFM) caused by target's velocity and acceleration. Then, matched filtering process is performed to compensate the phase error caused by target's jerk motion. Finally, the integration is achieved by summing signal data in different range frequency cells and performing a two-dimensional fast Fourier transform (FFT). The proposed method is applicable for low signal-to-noise ratio (SNR) environment. Compared with the GRFT algorithm, the proposed method has a close integration performance and a lower computational complexity. The effectiveness is validated by simulations and real-data processing results.     

并行任务可靠性约束下的资源最小化调度

可靠性是系统的一项重要质量指标,在安全关键的系统中极其重要.应用资源冗余的方式可以提高系统的可靠性,但会消耗更多的系统资源.研究了异构多处理器系统执行并行任务时最小化系统资源并保证可靠性的问题.首先以任务在各处理器上的平均最坏执行时间为参考,将系统可靠性目标转换为单个任务的可靠性目标,分别给出了非复制和复制情况下任务可靠性目标的计算方法;然后设计了一个可靠性约束下的资源最小化非复制算法,当给出的可靠性目标要求不高于系统可达到的最高可靠性时,该算法总能将任务分配到合适的处理器并使系统满足可靠性要求.由于非复制算法不能满足系统更高可靠性目标要求,最后设计了2个基于任务复制的算法.应用实际并行任务和随机生成的并行任务将提出的算法和MaxRe算法、RR算法以及MRCRG算法进行比较,实验结果表明：提出的算法在满足系统可靠性目标的同时消耗的资源更少.     

ROM: a reliability knowledge representation for collaborative system design

Designing systems that satisfy target reliability is a challenge because of complex assembly structures and logical connections, numerous components and associated failure modes, and multi-disciplinary considerations. To overcome these difficulties and to design reliable systems in a systematic way, we have developed a knowledge representation for system design-for-reliability (SDfR). It is called reliability object model (ROM). ROM includes (1) a new reliability analysis structure, (2) reliability metrics that consider both random failures and wear-out failures, (3) algorithms that allocate, predict, and assess reliability, and (4) rules for reliability-oriented design change recommendations. These capabilities of ROM are demonstrated by prototype SDfR tools and three electronic system case studies. The results show that ROM is an effective unified method for SDfR, providing richer semantics and increasing the chances of developing reliable designs.     

Real-time pre-processing system with hardware accelerator for mobile core networks

With the rapidly increasing number of mobile devices being used as essential terminals or platforms for communication, security threats now target the whole telecommunication infrastructure and become increasingly serious. Network probing tools, which are deployed as a bypass device at a mobile core network gateway, can collect and analyze all the traffic for security detection. However, due to the ever-increasing link speed, it is of vital importance to offload the processing pressure of the detection system. In this paper, we design and evaluate a real-time pre-processing system, which includes a hardware accelerator and a multi-core processor. The implemented prototype can quickly restore each encapsulated packet and effectively distribute traffic to multiple back-end detection systems. We demonstrate the prototype in a well-deployed network environment with large volumes of real data. Experimental results show that our system can achieve at least 18 Gb/s with no packet loss with all kinds of communication protocols.     

基于ASAAC标准的BIT设计

为满足航空电子系统的可测试性,降低航空电子系统测试维护成本,结合ASAAC标准设计一个机内自测试(BIT)系统。BIT利用自身资源对系统进行故障检测或隔离,采用总线层次化方法将BIT设计分为系统级、分系统级及模块级3层测试结构,并给出模块级测试的软硬件设计方案。测试结果表明,该系统能使测试与航电系统的健康管理和故障管理紧密结合,在满足测试覆盖率等技术指标的同时,提高航空电子系统可靠性与可测试性。     

一种嵌入式系统的可靠性测试与评价方法

使用Markov模型进行嵌入式系统的可靠性测评,能够明显地节约计算时间,并保证可靠性测评的准确性,因而越来越受到人们的关注。在Markov模型中,可以使用敏感性因子描述嵌入式系统可靠性,建立敏感性因子和测试资源的关联,为系统模块分配可靠性指标,把嵌入式系统的可靠性测试,转化为相应的优化问题。文中介绍了一种基于Markov模型的嵌入式系统可靠性测试与评价方法,包括测评框架、设计指标分配和敏感性分析等内容,说明如何依照可靠性测评框架对嵌入式系统进行可靠性测评。     

An efficient heuristic for reliability design optimization problems

This paper develops an efficient heuristic to solve two typical combinatorial optimization problems frequently met when designing highly reliable systems. The first one is the redundancy allocation problem (RAP) of series-parallel binary-state systems. The design goal of the RAP is to select the optimal combination of elements and redundancy levels to maximize system reliability subject to the system budget and to the system weight. The second problem is the expansion-scheduling problem (ESP) of multi-state series-parallel systems. In this problem, the study period is divided into several stages. At each stage, the demand is represented as a piecewise cumulative load curve. During the system lifetime, the demand can increase and the total productivity may become insufficient to assume the demand. To increase the total system productivity, elements are added to the existing system. The objective in the ESP is to minimize the sum of costs of the investments over the study period while satisfying availability constraints at each stage. The heuristic approach developed to solve the RAP and the ESP is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected subspace. Numerical results for the test problems from previous research are reported and compared. The results show the advantages of the proposed approach for solving both problems.