DiscreteEvent Systems and Their Optimization

In this paper, we investigate how to quantitatively evaluate the performance of state estimation in a discrete event system. We adopt stochastic automaton to quantitatively describe a discrete event system. With the stochastic automaton, we can calculate the probability of occurrence of any event sequence. We say that an event sequence (with sufficient length) is detectable if we can determine the current state and subsequent states of the system after the occurrence of the sequence. We then define the sum of probabilities of all detectable event sequences as a quantitative state estimation indicator. This indicator is the limit when the length of sequence goes to infinite. In order to calculate the limit, we augment the discrete event system into a larger automaton which includes the information of the discrete event system and all its state estimates. The augmented automaton is also a stochastic automaton and can be converted into a Markov Chain by removing all the event labels. The calculation of the limit is then translated into the calculation of the sum of probabilities of some states in the Markov Chain, which can be done efficiently.

The problem of fault diagnosis has become an active research topic in Discrete Event Systems, which can be applied into many different areas, such as communication networks, process control, flexible manufacturing systems, software engineering, etc. This brief explores the effect of communication delays on the event-based fault diagnosis in networked discrete event systems (NDESs), which can be modeled by finite state automata. Firstly, the framework of NDESs is introduced, and a novel concept of networked diagnosability ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Net$ </tex-math></inline-formula> -diagnosability) is formally defined. Subsequently, the necessary and sufficient conditions for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Net$ </tex-math></inline-formula> -diagnosability in the partially observable outputs are provided, and the corresponding <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Net$ </tex-math></inline-formula> -diagnosability can be verified by an effective diagnoser, which can be obtained by a constructed algorithm. Finally, an illustrative example is given to demonstrate the proposed method. The current results about networked diagnosability will be conducive to maintain the information security in the actual cyber-physical systems.

This paper provides a framework for approaching the problem of fault detection in large Communication Networks. Communication process are modeled as Discrete Event Systems (D.E.S.), so any fault will appear as a change of a D.E.S. Here we concentrate on the simplest case of Discrete Event systems, namely Finite State Machines (FSM).

Analysis of temporal performance of supervised discrete event systems

From the Publisher: What important research developments are under way in control science and engineering? What are key challenges in control technology applications to different domains? What new directions are being charted for control systems?Now practicing control engineers and students can find accessible answers to these multifaceted control issues without the intensive mathematical analysis usually found in control systems books. This all-in-one resource brings you state-of-the-art research results by contributors who are leading experts in control.You will find insightful introductions and discussions of future trends for a range of control technologies and applications, including:*Computer-aided control system design*Discrete event systems*Intelligent control*Industrial process control*Intelligent transportation systems. PERSPECTIVES IN CONTROL ENGINEERING is the one-stop volume you need to gain an overview of the latest advances in control systems.Sponsored by:IEEE Control Systems Society.

Optimal Computing Budget Allocation for regression with gradient information

One of the main concerns about implementing networked automation systems is ensuring its security against cyber attacks. In this paper, we consider networked automation systems abstracted as Discrete-Event Systems (DES), and consider cyber attacks where a malicious agent eavesdrops a network communication channel with the objective to gather information about the system behavior. It is important to remark that network security strategies used in Information Technology (IT) cannot be straightforwardly used in industrial networks, since the control of automation systems usually requires small communication delays, which limits the size of the data that can be transmitted in the communication network. In this paper, we introduce a new cryptographic scheme based on events, called event-based cryptography, where an event is defined as any change in the binary signals transmitted in the channel. We also present a necessary and sufficient condition that the event-based encryption function must satisfy to be used in the cryptographic scheme proposed in this paper, and present a class of encryption functions that can be modeled by Mealy automata. We also present procedures for the implementation of the event-based encryption function, and illustrate all results with a practical example.

Introduction to Discrete Event Systems is a comprehensive introduction to the field of discrete event systems, offering a breadth of coverage that makes the material accessible to readers of varied backgrounds. The book emphasizes a unified modeling framework that transcends specific application areas, linking the following topics in a coherent manner: language and automata theory, supervisory control, Petri net theory, Markov chains and queuing theory, discrete-event simulation, and concurrent estimation techniques. This edition includes recent research results pertaining to the diagnosis of discrete event systems, decentralized supervisory control, and interval-based timed automata and hybrid automata models.

A new method based on discrete event system is proposed for fault diagnosis of a certain kind of circuit, such as a relay control circuit. The original algorithm to obtain a minimal test set is improved. By using the improved algorithm the finest testable partition can be obtained and the complex testability analysis is avoided. The basic model of the proposed method and the general rule for fault diagnosis are described in detail. At first, the relay control circuit is described with corresponding combinational logic circuit model. Then, the fault diagnosis model of the circuit-under-test is constructed based on the given DES model. This method is applied to diagnose a relay control circuit. The results indicate that this method can diagnose this kind of circuit effectively and the new algorithm has a much lower computational complexity than the original algorithm. The fault elements can be localized exactly and this method has high practical value.

In this note, we introduce and study the notion of safety control of stochastic discrete-event systems (DESs), modeled as controlled Markov chains. For nonstochastic DESs modeled by state machines or automata, safety is specified as a set of forbidden states, or equivalently by a binary valued vector that imposes an upper bound on the set of states permitted to be visited. We generalize this notion of safety to the setting of stochastic DESs by specifying it as an unit-interval valued vector that imposes an upper bound on the state probability distribution vector. Under the assumption of complete state observation, we identify: 1) the set of all state feedback controllers that satisfy the safety requirement for any given safe initial state probability distribution, and 2) the set of all safe initial state probability distributions for a given state feedback controller.

Computer-integrated engineering systems are event-driven and often asynchronous, exhibiting concurrent, sequential, competitive and coordinated activities among their components. They are often complex and large in scale. These systems include integrated manufacturing systems, concurrent distributed systems, computer operating systems, communication networks, and intelligent machines. They fall into a class of systems called discrete event dynamic systems (DEDSs). The relations of events, their evolution over time and their order of appearance are of main interest. Compared with systems modeled as differential or difference equations, e.g. a manufacturing process, one has to deal with qualitative or abrupt changes characterized as events, instead of with quantitative changes in conventional continuous or discrete time systems. An investigation into the properties of and design methods for a DEDS has to start with an appropriate mathematical representation.

Residuals-based fault diagnosis of industrial automation systems using timed and untimed Interpreted Petri nets

In this paper we investigate control and management of power distribution networks modeled as timed and networked discrete event systems. We assume that the controller (the supervisor) communicates with the system to be controlled via a shared communication network, and that this network experiences bounded delays and losses that impact the controller. Under these assumptions, the necessary and sufficient condition for the existence of a controller is expressed as network controllability and network observability, which we define in the paper. We apply these results to a power distribution network, the IEEE 33-node (bus) test system, where the objective is to ensure the total substation transformer power stays within the given safety limits.

Response time is the key performance measure in on-line transaction processing systems and other client-server architectures. Not only is it important to achieve a low average value and correspondingly high throughput, but response time should also be fairly consistent in order to provide a good quality of service. We develop a new algorithm for computing the probability density function of response times in Markovian models of client-server systems. We model the clients and servers by central server queueing networks and obtain response time densities as simple functions of time under independence assumptions that are shown to hold asymptotically as network size increases. The communication network is modelled as a single server queue with mean service time determined by its operational characteristics. We consider an Ethernet and construct a new model, of interest in its own right, that captures details not modelled hitherto. This model is validated against simulation and shows good agreement up to moderate utilisations, the normal operating environment for Ethernets. The whole client-server model is implemented in the Metron Athene Client-Server capacity planning tool and sample runs are examined.

A discrete time queueing model for the performance of an ATM system is analyzed using matrix analytic methods. Time is segmented into slots with each slot equal to the transmission time of one ATM cell. The ATM system is modeled as a single server queue with Markovian arrivals and service time equal to one slot. The arrival process includes as a special case the superposition of on-off sources, possibly heterogeneous. The queueing model is of the M/G/1 type. By exploring the structure of the M/G/1 type Markov chain the complexity of the solution to the problem is reduced to only the inversion of a 2/spl times/2 matrix irrespective of the size of the Markov chain. This simplification allows us to solve problems of large sizes. In this paper, we generalize this basic model without losing much of the computational simplifications to the case where there are multiple states corresponding to k (k/spl ges/1) arrivals in a time slot (as opposed to a one-to-one mapping between the number of arrivals and the number of states in the Markov chain) providing a semi-Markov model for the number of arrivals.