基于Petri网结构分析的监控器综合

在基于Petri网建模的离散事件系统中, 提出利用局部关联信息进行约束转换, 并实现Petri网结构监控器综合的方法. 对以Parikh矢量约束形式给出的控制规范, 不可控不可观变迁会导致约束成为非法约束, 分析了不可控变迁的前向关联结构和不可观变迁的后向关联结构, 利用局部关联变迁实现对不可控和不可观变迁的间接控制, 从而将非法矢量约束转换为合法约束, 并保证初始控制规范的实现. 与基于矩阵的监控器综合方法相比, 本文的方法只需利用局部信息, 最后通过实例对该方法进行了说明.     

具有不确定动态线性系统的鲁棒状态估计

本文研究了一类具有参数和噪声特性不确定线性系统的鲁棒状态估计问题。利用对策论思想,定义了能使不确定下最坏性能最好的极小极大鲁棒状态估计器,提出了一种简单的近似设计方法,即设计最坏对象的最优滤波器。给出了这种设计方法设计滤波器导致的性能误差边界,进一步指出当满足文中给出的鞍点条件时,最坏对象的最优滤波器就是极小极大鲁棒滤波器。     

不确定线性系统有限时间状态估计与故障重构

针对具有外部干扰和执行器故障的不确定线性系统,给出了一种有限时间内估计系统状态及重构执行器故障的方法．首先,通过状态和输出等价变换,得到不受执行器故障和建模不确定信息干扰的降维解耦系统．在此基础上设计有限时间状态估计器,并设置任意小的时延参数,实现对降维系统状态的有限时间估计,从而达到对原系统状态有限时间估计的目的;其次,考虑高增益滑模微分器对系统输出微分进行有限时间估计;之后,在原系统状态和系统输出微分有限时间估计的基础上,提出一种对系统不确定信息和执行器故障同时估计的方法;最后,通过对具有执行器故障的F-16飞行器纵向系统模型进行仿真,验证所提方法的有效性．     

复杂网络的事件驱动故障估计

针对一类非线性耦合的复杂网络系统，提出了一种基于复杂网络估计器的近似最优故障估计方法.首先将复杂网络的状态与故障进行增广，然后对增广后的状态和故障进行了联合状态估计.为了处理多信号传输可能发生的数据冲突，采用了事件驱动的方法使复杂网络的输出传输至远程估计器.通过递推矩阵方程方法给出了估计误差协方差矩阵的上界，并通过设计估计器参数使得该上界在迹的意义下最小.最后，通过仿真例子验证了所提联合估计方案的可行性和有效性.     

带有随机通信时滞的状态估计

研究了测量值不带时间戳的网络控制系统的最优状态估计问题. 当最大的随机时滞界是一步滞后时, 对可能存在的乱序测量提出新的测量模型. 基于每一时刻收到的所有测量值的平均值构造估计器以保证不稳定网络控制系统的估计器是线性无偏的及估计误差协方差一致有界, 并通过求解离散黎卡提方程得到估计器增益. 在无偏性及误差协方差一致有界的意义下保证估计器是最优的. 最后给出仿真实例验证了该算法的有效性.     

离散系统状态和参数鲁棒滤波分离算法

提出了一种离散系统的鲁棒分离滤波方法.为了对状态向量进行较准确估计,将鲁棒滤波器分为:1)零误差状态估计器;2)不确定矩阵估计器;3)鲁棒合成器.零偏差状态估计器是假定系统的不确定部分为零时的状态估计器;其新息作为不确定部分的估计变量,并由此估计系统的不确定部分;最后,根据系统不确定部分估计误差的上下界,用鲁棒合成器对状态向量的估计值进行鲁棒修正.为了在合成器中得到鲁棒滤波的逼近计算式,通过变换状态估计误差的协方差阵,得到了系统矩阵不确定部分的误差上界不等式逼近,并且得到了估计误差协方差阵逆阵的下界不等式逼近,从而给出了鲁棒合成滤波的完整算法.     

2-D线性离散系统一般模型的最优状态估计*

本文利用最优状态估计理论，讨论了二维线性离散系统一般模型最优状态估计问题，基于２－ＤＧＭ的变结构１－Ｄ表示，导出了表现为１－Ｄ形式的２－ＤＧＭ的最优状态估计器，文中还直接由２－ＤＧＭ出发，将１－Ｄ最优状态估计的思想推广到２－Ｄ情形，提出了２－Ｄ状态估计器的设计方法。     

网络化最优预测状态估计

当网络诱导时延和数据包丢失确定可知时,提出了一种网络化最优预测状态估计器设计方法,能够补偿网络诱导时延和数据包丢失对估计性能的影响,理论分析表明了随着网络诱导时延或数据包丢失的增加,该估计器在获得明显补偿效果的同时预测估计偏差略微递增,并给出了估计系统的稳定性条件,最后通过仿真和实验验证了所提出方法的有效性和理论分析的正确性.     

具有Markovian时延与丢包的离散系统的状态估计

网络化控制系统中经常会因网络带宽有限而导致数据包在网络中传输时产生时延甚至丢失.本文主要研究具有Markovian时延与丢包的离散线性系统的状态估计问题.通过在估计器端设置适当长度的缓存器,把具有多状态Markovian时延与丢包的离散定常系统建模成数据包到达过程为两状态Markovian模型的离散时变系统,并基于跳跃线性估计器的思想提出了一类特殊的估计器,即限定接收历史估计器 (FRHE).在最大时延已知时,给出了可选增益的最优RHE设计策略.该策略虽然是次优,却能提供简便的计算.通过与时变Kalman估计器 (TVKE)的仿真对比,表明所提策略的有效性.     

扰动估计器的构造和设计

本文介绍了一种扰动估计器的构造和设计，它是渐近稳定的，能对有界、带限的不可测扰动作出实时估计，并可将估计误差控制在一定的范围内．该扰动估计器不要求受到扰动的受控系统是稳定的，也不要求受扰的受控系统处于闭环状态．仿真结果验证了该扰动估计器的有效性．     

Fault detection for discrete event systems using Petri nets with unobservable transitions

In this paper we present a fault detection approach for discrete event systems using Petri nets. We assume that some of the transitions of the net are unobservable, including all those transitions that model faulty behaviors. Our diagnosis approach is based on the notions of basis marking and justification, that allow us to characterize the set of markings that are consistent with the actual observation, and the set of unobservable transitions whose firing enable it. This approach applies to all net systems whose unobservable subnet is acyclic. If the net system is also bounded the proposed approach may be significantly simplified by moving the most burdensome part of the procedure off-line, thanks to the construction of a graph, called the basis reachability graph.     

Identification of the unobservable behaviour of industrial automation systems by Petri nets

This paper addresses the problem of identifying the model of the unobservable behaviour of discrete event systems in the industrial automation sector. Assuming that the fault-free system structure and dynamics are known, the paper proposes an algorithm that monitors the system on-line, storing the occurred observable event sequence and the corresponding reached states. At each event observation, the algorithm checks whether some unobservable events have occurred on the basis of the knowledge of the Petri net (PN) modelling the nominal system behaviour and the knowledge of the current PN marking. By defining and solving some integer linear programming problems, the algorithm decides whether it is necessary to introduce some unobservable (silent) transitions in the PN model and provides a PN structure that is consistent with the observed event string. A case study describing an industrial automation system shows the efficiency and the applicability of the proposed algorithm.     

On-line fault detection in discrete event systems by Petri nets and integer linear programming

The paper addresses the fault detection problem for discrete event systems in a Petri Net (PN) framework. Assuming that the structure of the PN model and the initial marking are known, faults are modelled by unobservable transitions. Moreover, we assume that there may be additional unobservable transitions associated with the system legal behaviour and that the marking reached after the firing of any transition is unknown. The proposed diagnoser works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition and solution of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. The results characterize the properties that the PN modelling the system fault behaviour has to fulfill in order to reduce the on-line computational effort.     

On-Line Monitoring of Large Petri Net Models Under Partial Observation

We consider a Petri Net model of the plant. The observation is given by a subset of transitions whose occurrence is always and immediately sensed by a monitoring agent. Other transitions not in this subset are silent (unobservable). Classical on-line monitoring techniques, which are based on the estimation of the current state of the plant and the detection of the occurrence of undesirable events (faults), are not suitable for models of large systems due to high spatial complexity (exponential in the size of the entire model). In this paper we propose a method based on the explanation of plant observation. A legal trace minimally explains the observation if it includes all unobservable transitions whose firing is needed to enable the observed transitions. To do so, starting from an observable transition, using backward search techniques, a set of minimal explanations is derived, which are sufficient for detecting whether a fault event must have occurred for sure in the plant or not. The technique also allows production of a set of basis markings for the estimation of the current state of the plant. The set of all possible current markings can then be characterized as the unobservable reach of these basis markings. The computational complexity of the algorithm depends on the size of the largest connected subnet which includes only unobservable transitions. This allows monitoring of plants of any size in which there is no large unobservable subnet. We also illustrate the applicability of the method for the monitoring of a class of infinite state systems, unbounded Petri Nets with unobservable trap circuits, and we show how this can be useful for distributed implementations.

Event‐triggered approach for finite‐time state estimation of delayed complex dynamical networks with random parameters

This article emphasizes the finite‐time state estimation problem for delayed complex dynamical networks with random parameters. In order to reduce the amount of transmission process, an aperiodic sampled‐data event‐triggered mechanism is introduced to determine whether the measurement output should be released at certain time points which incorporate an appropriate triggering condition and sampling moments. Furthermore, a concept of finite‐time boundedness in the pth moment is proposed to access the performance of state estimator. The objective of this article is to design an event‐triggered state estimator to estimate the states of nodes such that, in the presence of time delays, uncertainties, and randomly changing coupling weights, the estimation error system is finite‐time bounded in the pth moment related to a given constant. Some sufficient conditions in form of linear matrix inequalities and algebraic inequalities are established to guarantee finite‐time boundedness. Finally, a numerical example is presented to show the effectiveness of the theoretical results.     

On optimal control of a class of partially observed discrete event systems

We are interested in a new class of optimal control problems for discrete event systems. We adopt the formalism of supervisory control theory (Proc. IEEE 77(1) (1989) 81) and model the system as a finite state machine (FSM). Our control problem is characterized by the presence of uncontrollable as well as unobservable events, the notion of occurrence and control costs for events and a worst-case objective function. We first derive an observer for the partially unobservable FSM, which allows us to construct an approximation of the unobservable trajectory costs. We then define the performance measure on this observer rather than on the original FSM itself. We then use the algorithm presented in Sengupta and Lafortune (SIAM J. Control Optim. 36(2) (1998)) to synthesize an optimal submachine of the C-observer. This submachine leads to the desired supervisor for the system.     

Supervisory control of partially observable marked graphs

This note presents a control synthesis approach for discrete event systems modeled by marked graphs with unobservable transitions. It solves forbidden state problems characterized by a set of general mutual exclusion constraints. We prove that for any sequence of observable transitions, there exist a unique marking from which all other possible current markings can be reached unobservably. This salient feature allows us to design efficient control policies based on proper separation of observation and control.     

Control of Petri nets subject to strict temporal constraints using Max-Plus algebra

In this paper, we treat the control problem of timed discrete event systems under temporal constraints. This type of constraint is very frequent in production systems, transportation network and in networked automation systems. Precisely, we are interested in the validation of strict temporal constraints imposed on the paths in a timed event graph (TEG) by using Max-Plus algebra. Not all the transitions of the considered TEG model are controllable, i.e. only the input transitions are controllable. An analytical approach for computing state feedback controllers is developed. Sufficient condition is given for the existence of causal control laws satisfying the temporal constraints. In the first, a TEG with observable transitions is considered. Then, the proposed approach is extended to the partially observable TEG. The synthesised feedback can be interpreted by places of control connected to the TEG to guarantee the respect of the time constraints. The proposed method is illustrated in the assembly system example.     

Analysis of Hybrid Systems Based on Hybrid Net Condition/Event System Model

In thispaper, hybrid net condition /event systems are introducedas a model for hybrid systems. The model consists of a discretetimed Petri net and a continuous Petri net which interact eachother through condition and event signals. By introducing timeddiscrete places in the model, timing constraints in hybrid systemscan be easily described. For a class of hybrid systems that canbe described as linear hybrid net condition /eventsystems whose continuous part is a constant continuous Petrinet, two methods are developed for their state reachability analysis.One is the predicate-transformation method, which is an extensionof a state reachability analysis method for linear hybrid automata.The other is the path-based method, which enumerates all possiblefiring seqenences of discrete transitions and verifies if a givenset of states can be reached from another set by firing a sequenceof discrete transitions. The verification is performed by solvinga constraint satisfaction problem. A technique that adds additionalconstraints to the problem when a discrete state is revisitedalong the sequence is developed and used to prevent the methodfrom infinite enumeration. These methods provide a basis foralgorithmic analysis of this class of hybrid systems.