Automatically multi-paradigm requirements modeling and analyzing: An ontology-based approach

Requirements engineering (RE) is one of the crucial phases in software engineering (cf. ref. [1]). In the 1995 survey[1], 8000 projects undertaken in the whole country have been examined. The result indicated that one third of the projects were never completed and one half of the rest succeeded only partially. Poor requirements have been identified as the source of such failure (45%), in which the lack of user involvement (13%) and requirements incompleteness (12%) are the two major causes. R…     

An approach to information requirements specification for process control tasks

This paper discusses the need for designers of process plant supervisory systems to make greater effort in anticipating the information that operators require to carry out their duties. A method for dealing with this problem of information requirements specification in process plant design is proposed. This method translates a task analysis into a set of standard task elements from which standard sets of information, called ‘sub-goal templates’ can be derived. The resultant information requirements specification sets out the operators' information needs in the context of the operating goals that have to be attained. Early trials with the method indicate its promise, but highlight the need for its implementation in a computer tool to assist the designer. The features of such a tool and the further work necessary to develop and test the method are described.     

MOQARE: misuse-oriented quality requirements engineering

This work presents MOQARE (misuse-oriented quality requirements engineering), a method to explore quality requirements. The aim of MOQARE is to support intuitive and systematic identification of quality requirements. It was developed by integrating and adapting concepts from other methods (like Misuse Cases). It provides a general conceptual model of quality requirements, and a checklist-based process for deriving them in a top-down fashion. This derivation starts from business goals and vague quality requirements and delivers detailed requirements. MOQARE applies to requirements on the system to be developed requirements, but also derives requirements on the development process, including administration and maintenance. It considers normal and extreme use. The relationships among these requirements are modeled in a Misuse Tree. MOQARE has shown its merits in several case studies, one of which is presented here.     

Composite performance and dependability analysis

Composite performance and dependability analysis is gaining importance in the design of complex, fault-tolerant systems. Markov reward models are most commonly used for this purpose. In this paper, an introduction to Markov reward models including solution techniques and application examples is presented. Extensions of Markov reward models to semi-Markov reward models are also mentioned. A brief discussion of how task completion time models and models of queues with breakdowns and repairs relate to Markov reward models is also given.     

Averaging level control: An approach based on mass balance

Level control plays a fundamental role in the economic operation of many processes. This paper shows that interconnection and damping assignment passivity-based control, well known for electrical and mechanical applications, can be used to design high performance averaging level controllers for interconnected tank circuits, using physically motivated mass balance principles. The proposed method can deal with multiple tanks described by nonlinear dynamics with state constraints and rigourously establish the stability of the closed loop system. Furthermore, the transient behavior can be easily regulated, selecting the mass storage function assigned to the system, while keeping the control signal positive. As far as we know, none of the existing methods can address all these issues within a unifying framework. The simulation of a single tank and a multi-tank circuit illustrates the main issues raised in this paper.     

基于模型法应对企业信息系统工程中不确定性需求

在软件工程或具体的需求工程中,用户需求通常具有不确定性.这成为了企业信息化实践中的主要问题之一;在企业信息系统工程中这尤其是一关键问题.通过扩展模型的概念、分析企业领域中可用模型的情况,提出了一种基于模型来应对用户需求之不确定性的方法.描述了应用基于模型的方法确定企业信息系统需求的基本逻辑与主要活动过程,并给出了一个应用ARIS(集成信息系统结构)参考模型库解决需求问题的实例.研究表明,基于模型的方法可用于有效地应对企业信息系统工程中的不确定性需求.     

Multivariable closed-loop deadbeat control: a polynomial-matrix approach

The closed-loop deadbeat servo problem (CDSP), considered in this paper, consists of the synthesis of a linear, output feedback controller such that the control signal and tracking error both vanish, after a finite period of time, for every reference sequence from a prespecified class and for every initial state of a plant and the controller. The closed-loop structure is determined by studying necessary and sufficient conditions for deadbeat tracking performance. A new theorem asserts that if an open-loop deadbeat control strategy exists for every initial state of the plant and every reference function from a given class, then CDSP is solvable and all desired control laws are found in an explicit parametric form by solving simple, unilateral, linear equations in polynomial matrices. On the basis of this theorem a design algorithm is developed. Asymptotic stability of the closed-loop system exhibiting deadbeat properties is demonstrated. A numerical example is given to illustrate the usefulness and computational efficiency of the new design algorithm presented.     

Optimal control of nonlinear systems: a predictive control approach

A new nonlinear predictive control law for a class of multivariable nonlinear systems is presented in this paper. It is shown that the closed-loop dynamics under this nonlinear predictive controller explicitly depend on design parameters (prediction time and control order). The main features of this result are that an explicitly analytical form of the optimal predictive controller is given, on-line optimisation is not required, stability of the closed-loop system is guaranteed, the whole design procedure is transparent to designers and the resultant controller is easy to implement. By establishing the relationship between the design parameters and time-domain transient, it is shown that the design of an optimal generalised predictive controller to achieve desired time-domain specifications for nonlinear systems can be performed by looking up tables. The design procedure is illustrated by designing an autopilot for a missile.     

Suboptimal control for nonlinear systems: a successive approximation approach

This paper presents a successive approximation approach (SAA) designing optimal controllers for a class of nonlinear systems with a quadratic performance index. By using the SAA, the nonlinear optimal control problem is transformed into a sequence of nonhomogeneous linear two-point boundary value (TPBV) problems. The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term which is the limit of an adjoint vector sequence. By using the finite-step iteration of the nonlinear compensation sequence, we can obtain a suboptimal control law. Simulation examples are employed to test the validity of the SAA.     

Assessing critical functional and non-functional requirements for web-based procurement systems: a comprehensive survey

World Wide Web (WWW)-based electronic commerce has emerged as a mean to conduct business transactions that were previously handled through traditional interorganizational systems, phone, fax, on-site visits, or mail. Today, electronic procurement (e-procurement) accounts for most of the volume and value of the business transactions conducted over the Internet. As of yet, however, little or no research has assessed the functional and non-functional requirements sought for the WWW-based systems used to support the procurement process. This paper, presents findings of a survey of 133 corporate buyers from about 130 companies on the use of readily available web-based systems for business-to-business transactions and the requirements perceived to be critical to the effective support of supply chain operations.     

基于UMLsec的软件安全需求建模方法研究

安全性是现代软件系统的重要组成部分,安全需求建模是确保软件安全性的基础.针对软件安全需求,提出了一种基于UML安全扩展(UMLsec)的软件安全需求建模方法.在软件需求规格说明的基础上,获取安全需求,对安全需求进行描述,并将安全需求描述集成到功能需求模型中,构建安全需求模型,并对模型进行了验证.科研信息系统实例表明了该方法的有效性.     

Fault tolerance in supervisory control systems: a knowledge-based approach

Fault tolerance in computerized systems involved in production has become an ever more important requirement. Existing fault tolerance approaches, wherever used, deal mainly with hardware faults. Nevertheless, the vast majority of contemporary system failures are software related. This paper introduces a knowledge-based approach to handling software related faults occurring in supervisory control systems. These systems are event driven and use data, stored in complex databases, to react to events coming from different kinds of devices by identifying, scheduling, initiating and monitoring operations. Failure of part of the supervisory control system's software to behave rationally when unexpected events occur is called an application fault. The approach introduced in this paper is based on a supervisory control system reference model which reveals the set of all possible application faults together with the major functions of the recovery processes associated with each fault, and leads to a high-level knowledge-based system architecture capable of handling every fault-related condition. This system is called PROFIT (Intelligent PROduction systems Fault Tolerance) and consists of three main components: the fault diagnosis module, the instant fault correction module and the learning module, co-ordinated by a PROFIT meta-level module. The prototype version of PROFIT is analysed and the development as well as the run-time environment that prove the applicability and effectiveness of the system are presented.     

Invertibility of affine nonlinear control systems: a geometric approach

The paper deals with the invertibility of multivariable non-linear control systems. By using the recently developed theory on controlled invariant and controllability distributions necessary and sufficient conditions for invertibility are derived.     

On the model-based approach to nonlinear networked control systems

The problem of model-based stabilization of a nonlinear system based on its approximate discrete-time model is addressed, under the assumption that both the feedforward and the feedback paths are subject to network-induced constraints. These constraints include irregularity of the transfer intervals, time-varying communication delays, and the possibility of packet losses. A communication protocol that copes with these constraints is proposed. A “Stability+performance recovery” result for the nonlinear model-based networked control system (NCS) is formulated and proven.Simulation results presented confirm that the proposed method improves the maximum allowable transfer interval.     

基于信息特征的需求开发与管理研究

如何荻取用户的真正需求是需求工程的难点.需求工程是创造性的高层次知识活动,根据知识等级层次,信息最接近于事实且涉及专业知识最少.以信息方式交流需求具有容易理解的优势,便于减少和消除人们因知识背景不同而产生的交流困难.应用信息特征探讨了几点有效提高需求开发与管理效率的对策.     

Guaranteed cost nonlinear tracking control of a boiler-turbine unit: an LMI approach

This article addresses the problem of designing a guaranteed cost nonlinear state feedback tracking control for a boiler-turbine unit. First, the nonlinear boiler-turbine is re-expressed as a linear system with norm bounded uncertainties via a nonlinear transformation function. Then, based on this linear model a sufficient condition for the existence of a guaranteed cost nonlinear state feedback tracking control is derived in terms of linear matrix inequalities. The advantage of the proposed tracking control design is that only a simple nonlinear controller is constructed and it does not involve feedback linearisation technique and complicated adaptive or fuzzy schemes. An industrial boiler-turbine system is used to illustrate the effectiveness of the proposed design as compared with a linearised approach.     

A soft computing approach for privacy requirements engineering: The PriS framework

Soft computing continuously gains interest in many fields of academic and industrial domain; among the most notable characteristics for using soft computing methodological tools is the ability to handle with vague and imprecise data in decision making processes. Similar conditions are often encountered in requirements engineering. In this paper, we introduce the PriS approach, a security and privacy requirements engineering framework which aims at incorporating privacy requirements early in the system development process. Specifically, PriS provides a set of concepts for modelling privacy requirements in the organisation domain and a systematic way-of-working for translating these requirements into system models. The conceptual model of PriS uses a goal hierarchy structure. Every privacy requirement is either applied or not on every goal. To this end every privacy requirement is a variable that can take two values [0,1] on every goal meaning that the requirements constraints the goal (value 1) or not (value 0). Following this way of working PriS ends up suggesting a number of implementation techniques based on the privacy requirements constraining the respective goals. Taking into account that the mapping of privacy variables to a crisp set consisting of two values [0,1] is constraining, we extend also the PriS framework so as to be able to address the degree of participation of every privacy requirement towards achieving the generic goal of privacy. Therefore, we propose a fuzzification of privacy variables that maps the expression of the degree of participation of each privacy variable to the [0,1] interval. We also present a mathematical framework that allows the concurrent management of combined independent preferences towards the necessity of a privacy measure; among the advantages of the presented extended framework is the scalability of the approach in such a way that the results are not limited by the number of independent opinions or by the number of factors considered while reasoning for a specific selection of privacy measures.     

Stochastic iterative dynamic programming: a Monte Carlo approach to dual control

Practical exploitation of optimal dual control (ODC) theory continues to be hindered by the difficulties involved in numerically solving the associated stochastic dynamic programming (SDPs) problems. In particular, high-dimensional hyper-states coupled with the nesting of optimizations and integrations within these SDP problems render their exact numerical solution computationally prohibitive. This paper presents a new stochastic dynamic programming algorithm that uses a Monte Carlo approach to circumvent the need for numerical integration, thereby dramatically reducing computational requirements. Also, being a generalization of iterative dynamic programming (IDP) to the stochastic domain, the new algorithm exhibits reduced sensitivity to the hyper-state dimension and, consequently, is particularly well suited to solution of ODC problems. A convergence analysis of the new algorithm is provided, and its benefits are illustrated on the problem of ODC of an integrator with unknown gain, originally presented by Åström and Helmersson (Computers and Mathematics with Applications 12A (1986) 653-662).