离散事件系统基于模型诊断的研究进展

近年来,针对离散事件系统的基于模型诊断方法在大型通讯网络、电网故障诊断等领域获得了成功应用,成为人工智能与控制工程领域的热门研究课题。介绍了针对离散事件系统的基于模型诊断的基本思想与建模方法,从不同的角度对使用自动机建模的各种主要诊断方法进行了评析与比较;讨论了系统可诊断性判定方法的研究进展。从系统建模、分布式在线诊断、不完备模型下的诊断以及系统实现等方面,展望了针对离散事件系统的基于模型诊断领域中有待解决的问题。     

Potential cases, methodologies, and strategies of synthesis ofsolutions in distributed expert systems

In this paper, firstly, potential synthesis cases in distributed expert systems (DESs) and types of DESs are identified. Based on these results, necessary conditions of synthesis strategies in different synthesis cases are recognized. Secondly, two methodologies for designing synthesis strategies in DESs are investigated. They are analysis methods and inductive methods. Thirdly, two methodologies are discussed based on the viewpoints of performance, complexity and requirements     

Supervisory control of fuzzy discrete event systems: a formal approach.

Fuzzy discrete event systems (DESs) were proposed recently by Lin and Ying [19], which may better cope with the real-world problems of fuzziness, impreciseness, and subjectivity such as those in biomedicine. As a continuation of [19], in this paper, we further develop fuzzy DESs by dealing with supervisory control of fuzzy DESs. More specifically: 1) we reformulate the parallel composition of crisp DESs, and then define the parallel composition of fuzzy DESs that is equivalent to that in [19]. Max-product and max-min automata for modeling fuzzy DESs are considered, 2) we deal with a number of fundamental problems regarding supervisory control of fuzzy DESs, particularly demonstrate controllability theorem and nonblocking controllability theorem of fuzzy DESs, and thus, present the conditions for the existence of supervisors in fuzzy DESs; 3) we analyze the complexity for presenting a uniform criterion to test the fuzzy controllability condition of fuzzy DESs modeled by max-product automata; in particular, we present in detail a general computing method for checking whether or not the fuzzy controllability condition holds, if max-min automata are used to model fuzzy DESs, and by means of this method we can search for all possible fuzzy states reachable from initial fuzzy state in max-min automata. Also, we introduce the fuzzy n-controllability condition for some practical problems, and 4) a number of examples serving to illustrate the applications of the derived results and methods are described; some basic properties related to supervisory control of fuzzy DESs are investigated. To conclude, some related issues are raised for further consideration.     

基于粗糙集理论的离散事件系统不透明性的验证算法

近年来,离散事件系统的不透明性研究引起了国内外众多学者的广泛关注.本文针对离散事件系统的不透明性,提出了一种将粗糙集理论作为知识提取工具来处理离散事件系统不透明性验证的方法.先对离散事件系统的不透明性进行形式化,再利用粗糙集理论对离散事件系统以信息表及决策表的形式进行表示,得到一个关于离散事件系统不透明性的充分必要条件.在此基础上,给出一个验证离散事件系统不透明性算法.与现有方法相比,该验证算法既适用于对强不透明性的验证,又适用于对弱不透明性的验证,并且在时间复杂度上也有较明显改进.     

Diagnosability of Fuzzy Discrete-Event Systems: A Fuzzy Approach

In order to more effectively cope with the real-world problems of vagueness, fuzzy discrete-event systems (FDESs) were proposed by Lin and Ying recently. Then we and Cao and Ying investigated the supervisory control of FDESs independently. In this paper, we are concerned with another important issue of FDESs, the failure diagnosis. More specifically: (1) we propose a ldquofuzzy diagnosabilityrdquo approach by introducing a fuzzy diagnosability function to characterize the diagnosability degree, which takes values in the interval [0,1] rather than { 0,1}; (2) based on the observability of events, we formalize the construction of the diagnosers that are used to perform fuzzy diagnosis; (3) a number of basic properties of the diagnosers are investigated. In particular, we present a necessary and sufficient condition for failure diagnosis of FDESs. Our results generalize the important consequences of the diagnosability for crisp discrete-event systems (DESs) introduced by Sampath et al. The newly proposed approach allows us to deal with the problem of diagnosability for both crisp DESs and FDESs; (4) in addition, a method for checking the fuzzy diagnosability for FDESs is proposed. Also, some examples are provided to illustrate the application of the diagnosability of FDESs.     

分布式模糊离散事件系统的故障预测

本文研究分布式模糊离散事件系统的故障预测问题.先根据系统的模糊特性,提出一种分布式模糊离散事件系统的协同可预测性的形式化方法,使分布式模糊离散事件系统的协同可预测度不小于各分站点的局部可预测度.通过构造协同预测验证器,提出一种基于协同预测验证器的协同预测算法,并得到一个关于分布式模糊离散事件系统协同可预测性的充分必要条件.     

A bridged diagnostic method for the monitoring of polymorphic discrete-event systems.

Diagnosis of discrete-event systems (DESs) is a challenging problem that has been tackled both by automatic control and artificial intelligence communities. The relevant approaches share similarities, including modeling by automata, compositional modeling, and model-based reasoning. This paper aims to bridge two complementary approaches from these communities, namely, the diagnoser approach and the active system approach, respectively. The more significant shortcomings of such approaches are, on the one side, the need for the generation of the global system model and, on the other, the lack of monitoring capabilities. The former makes the application of the diagnoser approach prohibitive in real contexts, where the system model is too large to be generated, even offline. The latter requires the completion of the system observation before starting the diagnostic task, thereby, making the monitoring of the system. impossible. The bridged diagnostic method subsumes, to a large extent on the peculiarities of the two approaches and is capable of coping with an extended class of DESs that integrate both synchronous and asynchronous behavior. The bridge is built by extending the active system approach by means of several enhanced techniques, which eventually, allow the efficient monitoring of polymorphic DESs. Upon the occurrence of each system message, two pieces of diagnostic information are generated, namely, the snapshot and historic diagnostic sets. While the former accounts for the faults pertinent to the newly generated message only, the latter is based on the whole sequence of messages yielded by the system during operation.     

On controlling prioritized discrete event systems with real-time constraints

We study a class of prioritized Discrete Event Systems (DESs) that involve the control of resources allocated to tasks under real-time constraints. Our work is motivated by applications in communication systems, computing systems, and manufacturing systems where the objective is to minimize energy consumption while guaranteeing that task deadlines are always met. In the off-line setting, we discover several structural properties of the optimal sample path of such DESs. Using the structural properties, we also propose a greedy algorithm which is shown numerically near optimal. For on-line control, we design a Receding Horizon (RH) controller. Using worst-case estimation, the RH control is able to guarantee feasibility (when the off-line problem is feasible) and achieve good performance.     

分层离散事件系统的不透明性

针对离散事件系统（DES）的不透明性问题，结合具有分层（hierarchical）结构的自动机模型，提出了分层离散事件系统的不透明性.对分层离散事件系统进行标准化，给出了分层离散事件系统不透明性和K延迟不透明性两个概念.为了对分层离散事件系统的两种不透明性进行验证，分别构造了两种相应的不透明性验证器，得到了关于不透明性和K延迟不透明性的充分必要条件，并对构造不透明性验证器的复杂度进行了分析.     

Robust and fault-tolerant supervisory control of discrete event systems with partial observation and model uncertainty

This paper proposes the notions of faults and failures in discrete event systems (DESs) with partial observation. They are associated with controllability and an observability property. The proposed notions are used to address the notion of tolerable fault event sequences which represents fault-tolerant behaviour of systems as a desired specification. A robust and fault-tolerant supervisor is a controller which is robust to model uncertainty and guarantees fault-tolerant behaviour of a system. In this paper we present necessary and sufficient conditions for the existence of a robust and fault-tolerant supervisor. The developed conditions capture the concepts of controllability and observability which are cores in the control of DESs with partial observation     

分布式随机离散事件系统的模式故障预测EI北大核心CSCD

本文以随机自动机为模型,研究分布式随机离散事件系统的模式故障预测问题.首先根据分布式随机离散事件系统的分布特性对模式故障协同可预测性概念进行形式化,并通过构造模式故障识别器来识别系统中发生的模式故障.然后,构造一个模式故障协同预测器,提出一种基于协同预测器的具有多项式复杂度的算法,得到关于分布式随机离散事件系统模式故障协同可预测性的充分必要条件,实现对分布式随机离散事件系统的模式故障预测.     

Controller and observer design for a class of discrete-time nonlinear switching systems

The main contribution of this paper is to present some controller synthesis results for the discrete-time nonlinear (Lipschitz-like) switching systems. Under the assumption that the discrete state of switching systems is known, three related problems are considered, which are full-state feedback controller design, continuous state observer design, and observer-based output feedback controller design. The basic idea of the proposed approaches is to construct the different types of Hybrid Lyapunov function to guarantee the stability, and all of these methods are given in terms of linear matrix inequalities. The results obtained in this paper are only dependent on the Lipschitz-like constant matrices without regard to the specific nonlinear forms. Finally, a numerical example made up of two subsystems is given to show the applicability of theoretical results.     

具有多项式时间复杂性的离散事件系统安全诊断

离散事件系统的故障诊断能将已发生的不可观故障事件及时诊断出来,但往往容易忽略故障诊断期间系统的安全性.为解决这一问题,提出了一种具有多项式时间复杂性的安全故障诊断方法.先对离散事件系统的安全可诊断性进行了形式化,再通过构造一个非法语言识别器对系统被禁止操作序列进行识别,并在此基础上构建了一个对系统实施安全诊断的安全验证器,得到了一个关于离散事件系统安全可诊断性的充分必要条件,实现了对系统的安全故障诊断.同时,通过对安全验证器的构建与安全可诊断性的判定的复杂性分析,得到了该安全故障诊断方法可在多项式时间内实现等结论.     

Adaptive Controller Design for Unknown Systems Using Measured Data

This paper presents a measurement‐based adaptive control design approach for unknown systems working over a wide range of operating conditions. Traditional control design approaches usually require the availability of a mathematical model. However, it has been shown in many practical situations that, due to complex dynamics of physical systems, some simplifying assumptions are made for the derivation of mathematical models. Hence, controller design based on simplified models may result in degradation of the desired closed‐loop performance. Data‐based control design approaches can be viewed as an alternative approach to model‐based methods. Most data‐based control methods available in the literature aim to design controllers for unknown systems that operate only at a given operating point. However, the dynamical behavior of plants may change for different operating conditions, which makes the task of designing a controller that works over the entire range of operating conditions more challenging. In this paper, we address such a problem and propose to design adaptive controllers based on measured data. Such a proposed method is based on designing a set of measurement‐based controllers validated at a finite set of pre‐specified operating points. Then, the parameters of the adaptive controller are obtained by interpolating between the set of pre‐designed controller parameters to derive a gain‐scheduling controller. Moreover, low‐order adaptive controllers can be designed by simply selecting the desired controller structure. The efficacy of the proposed approach is experimentally validated through a practical application to control a heating system operated over a large range of flow rate.     

基于动态观测的随机离散事件系统故障诊断

近年来,离散事件系统故障诊断研究引起国内外学者广泛关注.鉴于此,研究动态观测下随机离散事件系统的故障诊断.首先引入一种动态观测,使事件的可观测性随着系统的运行而动态变化;然后分别对基于动态观测的随机离散事件系统的单故障可诊断性和模式故障可诊断性进行形式化;最后通过构造相应的诊断器,分别得到关于单故障可诊断性和模式故障可...     

The computer-aided design of microwave matching networks

Matching networks, as used between the consecutive stages of an amplifier to manage the transfer of power between the complex source impedance, the active devices, and the load, continue to be of importance, particularly in microwave systems. Synthesis techniques for these networks have evolved from the classical theory to novel numerical approaches that yield significant practical advantages. We review here several well-known design methods, including the classical derivation, sloped-approximation synthesis, and the real-frequency technique. Also considered are enhancements and variations of these methods. Furthermore, we describe the iterated analysis approach, which appears to provide the greatest design flexibility, efficiency, and accuracy to date. Examples are given which illustrate the relative merits of some of the more modern computer-assisted techniques. Finally, we discuss ideas for further research in the area of matching network synthesis.     

An Efficient Algorithm for Solving Fuzzy Linear Programming Problems

In this article, we consider some well-known approaches for solving fuzzy linear programming (FLP) problems. We present some of the difficulties of these approaches. Then, crisp linear programming problems are suggested for solving FLP problems. A new algorithm is also given. The proposed approach has advantages over the other methods. For example, we can achieve higher membership degrees for objective function and constraints. Moreover, we show that the fuzzy optimal solutions obtained by the proposed approach are efficient enough. Also, we see that unlike the previous methods, our method finds efficient solutions by solving only one crisp linear problem instead of solving two or three crisp problems. Finally some numerical examples are presented to show the efficiency of the given approach over the other approaches.     

Periodically time-varying memory state-feedback controller synthesis for discrete-time linear systems

In this paper, we deal with discrete-time linear periodic/time-invariant systems with polytopic-type uncertainties and propose a new linear matrix inequality (LMI)-based method for robust state-feedback controller synthesis. In stark contrast with existing approaches that are confined to memoryless static controller synthesis, we explore dynamical controller synthesis and reveal a particular periodically time-varying memory state-feedback controller (PTVMSFC) structure that allows LMI-based synthesis. In the context of robust controller synthesis, we prove rigorously that the proposed design method encompasses the well-known extended-LMI-based static controller synthesis methods as particular cases. Through numerical experiments, we demonstrate that the suggested design method is indeed effective in achieving less conservative results, under both periodic and time-invariant settings. We finally derive a viable test to verify that the designed robust PTVMSFC is “exact” in the sense that it attains the best achievable robust performance. This exactness verification test works fine in practice, and we will show via a numerical example that exact robust control is indeed attained by designing PTVMSFCs, even for such a problem where the standard memoryless static state-feedback fails.     

离散事件系统间歇性故障的安全诊断

离散事件系统的间歇性故障诊断能够将系统中发生的间歇性故障及时诊断出来,但在诊断期间的系统可能会执行不安全操作.针对间歇性故障在诊断期间的安全性问题,提出一种基于事件的安全诊断方法.首先对发生间歇性故障的离散事件系统进行建模,并给出系统间歇性故障的安全可诊断性的形式化定义.然后通过构造非法语言识别器对系统的非法操作进行识别,并在此基础上构建一个安全验证器,由此得到一个关于系统间歇性故障安全可诊断性的充分必要条件,实现离散事件系统对间歇性故障的安全诊断.这种安全诊断既保证了间歇性故障一旦发生即能被及时诊断出来,又确保了在故障诊断期间系统不会执行任何不安全操作.     

Hybridization methods for the analysis of nonlinear systems

In this article, we describe some recent results on the hybridization methods for the analysis of nonlinear systems. The main idea of our hybridization approach is to apply the hybrid systems methodology as a systematic approximation method. More concretely, we partition the state space of a complex system into regions that only intersect on their boundaries, and then approximate its dynamics in each region by a simpler one. Then, the resulting hybrid system, which we call a hybridization, is used to yield approximate analysis results for the original system. We also prove important properties of the hybridization, and propose two effective hybridization construction methods, which allow approximating the original nonlinear system with a good convergence rate.