Verification of approximate opacity for switched systems: A compositional approach

The security in information-flow has become a major concern for cyber–physical systems (CPSs). In this work, we focus on the analysis of an information-flow security property, called opacity. Opacity characterizes the plausible deniability of a system’s secret in the presence of a malicious outside intruder. We propose a methodology of checking a notion of opacity, called approximate opacity, for networks of discrete-time switched systems. Our framework relies on compositional constructions of finite abstractions for networks of switched systems and their approximate opacity-preserving simulation functions. Those functions characterize how close concrete networks and their finite abstractions are in terms of the satisfaction of approximate opacity. We show that such simulation functions can be obtained compositionally by assuming some small-gain type conditions and composing local simulation functions constructed for each switched subsystem separately. Additionally, assuming certain stability property of switched systems, we also provide a technique on constructing their finite abstractions together with the corresponding local simulation functions. Finally, we illustrate the effectiveness of our results through an example.     

Rigid–flexible interactive dynamics modelling approach

Dynamics modelling of multi-body systems composed of rigid and flexible elements is elaborated in this article. The control of such systems is highly complicated due to severe underactuated conditions caused by flexible elements and an inherent uneven non-linear dynamics. Therefore, developing a compact dynamics model with the requirement of limited computations is extremely useful for controller design, simulation studies for design improvement and also practical implementations. In this article, the rigid–flexible interactive dynamics modelling (RFIM) approach is proposed as a combination of Lagrange and Newton–Euler methods, in which the motion equations of rigid and flexible members are separately developed in an explicit closed form. These equations are then assembled and solved simultaneously at each time step by considering the mutual interaction and constraint forces. The proposed approach yields a compact model rather than a common accumulation approach that leads to a massive set of equations in which the dynamics of flexible elements is united with the dynamics equations of rigid members. The proposed RFIM approach is first detailed for multi-body systems with flexible joints, and then with flexible members. Then, to reveal the merits of this new approach, few case studies are presented. A flexible inverted pendulum is studied first as a simple template for lucid comparisons, and next a space free-flying robotic system that contains a rigid main body equipped with two manipulating arms and two flexible solar panels is considered. Modelling verification of this complicated system is vigorously performed using ANSYS and ADAMS programs. The obtained results reveal the outcome accuracy of the new proposed approach for explicit dynamics modelling of rigid–flexible multi-body systems such as mobile robotic systems, while its limited computations provide an efficient tool for controller design, simulation studies and also practical implementations of model-based algorithms.     

冷备系统可靠性评定的统计方法

贮备是提高系统可靠性可行且有效的途径.关于冷备系统的可靠性评定问题,前人仅在设备均为指数型部件的情况给出了WCF方法.文中对实际中常用的指数-威布尔混合型冷备系统,提出了两种可靠性评定方法:WCF方法和Fiducial方法,并在中小样本下对两种方法进行了模拟研究,说明了这两种方法的实用性.     

Parametric study of nonlinear adaptive control algorithm with magneto-rheological suspension systems

This paper describes the details of the simulation analysis of a nonlinear model-based adaptive suspension control system [Song X, Ahmadian M, Southward SC, Miller LR. An adaptive semiactive control algorithm for magneto-rheological suspension systems. ASME J Vibr Acoust, in press; Song X. Design of adaptive vibration control systems with application of magneto-rheological dampers. Dissertation, Virginia Tech, December, 1999]. The numerical aspect of the simulation study of a seat suspension with application of magneto-rheological dampers will be presented. Magneto-rheological (MR) dampers have strong nonlinearities such as bi-linearity, hysteresis, and saturation related to magnetism, which can be represented by appropriate mathematic functions, respectively. Thus the model-based adaptive algorithm becomes complicated because of involvement of MR damper models. One objective of this study is to investigate the effect of MR damper model simplifications on the adaptive suspension performance. Furthermore, simulation is also applied to do parametric study of adaptive algorithm parameters such as filtering and step size. The numerical results compare the proposed adaptive controller with passive dampers to validate not only its effectiveness but also obtain some guidance information for its experimental implementation.     

Integrated decision support for aviation safety inspectors

This paper presents a systems viewpoint for developing an advanced decision support system for aircraft safety inspectors. Research results from a Federal Aviation Administration (FAA) sponsored project to use neural network and expert systems technology to analyze aircraft maintenance databases are summarized. One of the main objectives of this research is to define more refined “alert” indicators for national comparison purposes that can signal potential problem areas by aircraft type for safety inspector consideration.

Integration aspects are addressed on two levels: (1) integration of the various technical components of the decision support system, and (2) integration of the decision support system with individual behavior, management systems and organizational structure, as well as corporate culture across both formal and informal dimensions. The paper summarizes the creation of strategic “inspection profiles” for aging aircraft and reliability curve fitting for structural components both based upon using neural network technology. Also, the potential use of a model-based expert system to facilitate field inspection diagnostics is presented. Finally, a framework for developing an intelligent decision system to support aircraft safety inspections is proposed that links expert systems, neural networks, as well as a paradigm of the decision making process typically used in unstructured situations.     

Comparisons of series and parallel systems with components sharing the same copula

The paper is devoted to study stochastic comparisons of series and parallel systems with vectors of component lifetimes sharing the same copula. We show that, under some conditions on the common copula, the series system with heterogeneous components is worse than the series system with homogeneous components having a common reliability function, which is equal to the average of the reliability functions of the heterogeneous components. However, we show that this property is not necessarily true for arbitrary copulas. We obtain similar properties for parallel systems and for general coherent systems. For these purposes, we introduce in our analysis the notion of the mean function of a copula. Copyright © 2009 John Wiley & Sons, Ltd.     

Fuzzy temporal fault tree analysis of dynamic systems

Fault tree analysis (FTA) is a powerful technique that is widely used for evaluating system safety and reliability. It can be used to assess the effects of combinations of failures on system behaviour but is unable to capture sequence dependent dynamic behaviour. A number of extensions to fault trees have been proposed to overcome this limitation. Pandora, one such extension, introduces temporal gates and temporal laws to allow dynamic analysis of temporal fault trees (TFTs). It can be easily integrated in model-based design and analysis techniques. The quantitative evaluation of failure probability in Pandora TFTs is performed using exact probabilistic data about component failures. However, exact data can often be difficult to obtain. In this paper, we propose a method that combines expert elicitation and fuzzy set theory with Pandora TFTs to enable dynamic analysis of complex systems with limited or absent exact quantitative data. This gives Pandora the ability to perform quantitative analysis under uncertainty, which increases further its potential utility in the emerging field of model-based design and dependability analysis. The method has been demonstrated by applying it to a fault tolerant fuel distribution system of a ship, and the results are compared with the results obtained by other existing techniques.     

Conflict-directed A and its role in model-based embedded systems

Artificial Intelligence has traditionally used constraint satisfaction and logic to frame a wide range of problems, including planning, diagnosis, cognitive robotics and embedded systems control. However, many decision making problems are now being re-framed as optimization problems, involving a search over a discrete space for the best solution that satisfies a set of constraints. The best methods for finding optimal solutions, such as A^*, explore the space of solutions one state at a time. This paper introduces conflict-directed A^*, a method for solving optimal constraint satisfaction problems. Conflict-directed A^* searches the state space in best first order, but accelerates the search process by eliminating subspaces around each state that are inconsistent. This elimination process builds upon the concepts of conflict and kernel diagnosis used in model-based diagnosis [J. de Kleer, B.C. Williams, Diagnosing multiple faults, Artif. Intell. 32(1) (1987) 97-130; J. de Kleer, A. Mackworth, R. Reiter, Characterizing diagnoses and systems, Artif. Intell. 56 (1992) 197-222] and in dependency-directed search [R. Stallman, G.J. Sussman, Forward reasoning and dependency-directed backtracking in a system for computer-aided circuit analysis, Artif. Intell. 9 (1977) 135-196; J. Gaschnig, Performance measurement and analysis of certain search algorithms, Technical Report CMU-CS-79-124, Carnegie-Mellon University, Pittsburgh, PA, 1979; J. de Kleer, B.C. Williams, Back to backtracking: controlling the ATMS, in: Proceedings of AAAI-86, 1986, pp. 910-917; M. Ginsberg, Dynamic backtracking, J. Artif. Intell. Res. 1 (1993) 25-46]. Conflict-directed A^* is a fundamental tool for building model-based embedded systems, and has been used to solve a range of problems, including fault isolation [J. de Kleer, B.C. Williams, Diagnosing multiple faults, Artif. Intell. 32(1) (1987) 97-130], diagnosis [J. de Kleer, B.C. Williams, Diagnosis with behavioral modes, in: Proceedings of IJCAI-89, 1989, pp. 1324-1330], mode estimation and repair [B.C. Williams, P. Nayak, A model-based approach to reactive self-configuring systems, in: Proceedings of AAAI-96, 1996, pp. 971-978], model-compilation [B.C. Williams, P. Nayak, A reactive planner for a model-based executive, in: Proceedings of IJCAI-97, 1997] and model-based programming [M. Ingham, R. Ragno, B.C. Williams, A reactive model-based programming language for robotic space explorers, in: Proceedings of ISAIRAS-01, 2001].     

多源点多汇点网络系统可靠度的解析表示

本文研究了基于最小路径描述的多源点多汇点网络系统可靠性问题。定义了最小路径矩阵的几种运算,利用所定义的运算,将多源点多汇点网络系统转化为等价的单源点单汇点网络系统,并给出了由子系统可靠度精确表示网络系统可靠度的解析表达式。这种解析表达是非常重要的,它是系统可靠性的理论研究与实际应用的一个极为有效的工具。     

Reliability analysis of 1-for-2 shared protection systems with general repair-time distributions

In this paper, we investigate the reliability of a type of 1-for-2 shared protection systems. The 1-for-2 shared protection system is the most basic fault-tolerant configuration with shared backup units. We assume that there are two working units each serving a single user and one shared protection (spare) unit in the system. We also assume that the times to failure and to repair are subject to exponential and general distributions respectively. Under these assumptions, we derive the Laplace transform of the survival function (the cdf that the system will survive beyond a given time) for each user as well as the user-perceived Mean Time to First Failure (MTTFF) by combining the state transition analysis and the supplementary variable method. We also show the effect of the repair-time distribution, the failure rates and the repair rates of the units through the case study of small-sized two enterprises that share one spare device for backup purpose. The analysis reveals what is important and what should be done in order to improve the user-perceived reliability of shared protection systems.     

A constraint generation scheme to probabilistic linear problems with an application to power system expansion planning

In this paper, we first describe a constraint generation scheme for probabilistic mixed integer programming problems. Next, we present a decomposition approach to the peak capacity expansion planning of interconnected hydrothermal generating systems, with bounds on the transmission capacity between the regions. The objective is to minimize investments in generating units and interconnection links, subject to constraints on supply reliability. The problem is formulated as a stochastic integer program. The constraint generation scheme, which is similar to Benders decomposition, is applied in the solution of the peak capacity expansion problem. The master problem in this decomposition scheme is an integer program, solved by implicit enumeration. The operating subproblem corresponds to a stochastic network flow problem, and is solved by a maximum flow algorithm and Monte Carlo simulation. The approach is illustrated through a case study involving the expansion of the system of the Brazilian Southeastern region.     

Investigation of inverse simulation for design of feedforward controllers

This paper describes the use of inverse simulation to develop feedforward controllers for model-based output-tracking control system structures, thus avoiding the more complicated techniques of model inversion. Similarities and shortcomings of the inverse simulation and model inversion approaches are explored. It is found that, with suitable values of discretized time interval, the method based on inverse simulation may be preferable for minimum-phase systems. Depending upon zero redistribution within the process of inverse simulation, non-minimum-phase problems for linear systems can also be handled. The conclusions are demonstrated using a non-linear HS125 aircraft model, a linearised Lynx helicopter model and a container ship model for ship steering control and roll stabilization.     

Reliability inference with extended sequential order statistics

In this article, we will address the complexity of non-identical components in multi-component systems. Most technical systems can be described as such since either component types or component functions within the system vary amongst components. While most reliability related work resorts to the assumption of homogeneous components, we aim to address the often more realistic assumption of heterogeneous components extending the model of Extended Sequential Order Statistics by two inferential methods. Firstly, the derivation of Maximum Likelihood Estimates including a simulation study demonstrating their good performance for large enough sample size. Secondly, we introduce a likelihood ratio test to test whether components can be assumed identical accompanied by a power study. Both methods are powerful tools in reliability contexts. The former increases our understanding of component behaviour, especially upon failure of other components. This knowledge empowers system operators to make better decisions regarding maintenance schedules and failure time prediction. The latter supports operators in their quest of identifying component equivalence. Therefore, both methods can be used to achieve meaningful results in real life applications.     

A new approach for parameter estimation of finite Weibull mixture distributions for reliability modeling

The aim of this paper is to model lifetime data for systems that have failure modes by using the finite mixture of Weibull distributions. It involves estimating of the unknown parameters which is an important task in statistics, especially in life testing and reliability analysis. The proposed approach depends on different methods that will be used to develop the estimates such as MLE through the EM algorithm. In addition, Bayesian estimations will be investigated and some other extensions such as Graphic, Non-Linear Median Rank Regression and Monte Carlo simulation methods can be used to model the system under consideration. A numerical application will be used through the proposed approach. This paper also presents a comparison of the fitted probability density functions, reliability functions and hazard functions of the 3-parameter Weibull and Weibull mixture distributions using the proposed approach and other conventional methods which characterize the distribution of failure times for the system components. GOF is used to determine the best distribution for modeling lifetime data, the priority will be for the proposed approach which has more accurate parameter estimates.     

Modelling redundancy allocation for a fuzzy random parallel-series system

Due to subjective judgment, imprecise human knowledge and perception in capturing statistical data, the real data of lifetimes in many systems are both random and fuzzy in nature. Based on the fuzzy random variables that are used to characterize the lifetimes, this paper studies the redundancy allocation problems to a fuzzy random parallel-series system.Two fuzzy random redundancy allocation models (FR-RAM) are developed through reliability maximization and cost minimization, respectively. Some properties of the FR-RAM are obtained, in which an analytical formula of reliability with convex lifetimes is derived and the sensitivity of the reliability is discussed. To solve the FR-RAMs, we first address the computation of reliability. A random simulation method based on the derived analytical formula is proposed to compute the reliability with convex lifetimes. As for the reliability with nonconvex lifetimes, the technique of fuzzy random simulation together with the discretization method of fuzzy random variable is employed to compute the reliability, and a convergence theorem of the fuzzy random simulation is proved. Subsequently, we integrate the computation approaches of the reliability and genetic algorithm (GA) to search for the approximately optimal redundancy allocation of the models. Finally, some numerical examples are provided to illustrate the feasibility of the solution algorithm and quantify its effectiveness.     

利用组合群验数学模型分析汽车故障

利用组合群验的理论和方法建立数学模型,依据汽车可靠度对汽车系统定量分析,为确定故障部位,汽车维修,故障分析提供方法.     

Financial systems: a few theoretical and algebraic considerations for their modeling

In this paper I suggest that observable entities, usually named ‘financial systems’, may be related to the general conceptual framework of systems theory. Starting from the requisite properties of a (general) system, I derive a strong and operational concept for specific financial systems (Section 1). Then a general modeling procedure is proposed, mainly based upon graph theory (with an additional and complementary use of linear systems analysis), through which it is possible to establish the general static and almost dynamic properties of these specific systems and their implications for financial analysis itself (Section 2). A numerical example (Section 3) illustrates most of the concepts and ideas introduced throughout the paper.     

A survey of the perturbation analysis of discrete event dynamic systems

This paper introduces an analysis and optimization technique for discrete event dynamic systems, such as flexible manufacturing systems (FMSs), and other discrete part production processes. It can also be used for enhancement of the simulation results of, or the monitoring of the operations of such systems in real time. Extensive references are given where readers may pursue futher details.     

Numerical solution of the fractional-order Vallis systems using multi-step differential transformation method

In this paper, we examine a fractional order Vallis systems. We also fulfil a detailed analysis on the stability of equilibrium. Multi-step differential transform method (MsDTM) extends to give approximate and analytical solutions of a fractional order Vallis systems. Numerical simulations are submitted to verify the validity and reliability results obtained from these methods.     

Reliability assessment for load‐sharing systems with exponential components using statistical expansion as a correction

Among recent system models, one specific type of system is generally used to model the dependence among components. Components are connected parallel in such systems as they fail one by one and are supposed to share the system work load. The model is thus referred to as the load‐sharing system model. Despite the availability of extensive reliability assessment methods for different systems, load‐sharing systems have not received enough attention from the scholars who have studied reliability assessment so far. Load‐sharing systems are generally designed for high levels of reliability. Therefore, tests for such systems can be expensive and time consuming. Limitation on resources always leads to small test sample sizes. This increases the difficulties associated with obtaining an accurate and robust system reliability assessment result. This paper proposes a novel assessment method for a certain type of load‐sharing system with components following exponential lifetime distributions. Based on the parameter estimation of the system reliability model, we introduce the Winterbottom‐Cornish‐Fisher asymptotic expansion method for implementing a correction of normal approximation. We demonstrate the accuracy of our method through a series of examples and simulation studies.