Showing papers on "Discrete event dynamic system published in 2010"

Efficient Simulation Method for General Assembly Systems With Material Handling Based on Aggregated Event-Scheduling

Abstract: Performance evaluation of complex manufacturing systems is challenging due to many factors such as system complexity, parameter uncertainties, problem size, just to name a few. In many cases when a system is too complex to model using mathematical formulas, simulation is used as an effective alternative to conduct system analysis. A manufacturing system is a good example of such cases where both system performance and system complexity are greatly impacted by material handling (MH) strategy, management, and operational control. In this paper, we study vehicle general assembly (GA) system with MH, and focus on developing an efficient simulation method for modeling and analysis where traditional simulation methods may suffer from computation intensity. Making use of the partial system decomposability, we introduce an aggregated event-scheduling simulation method with two-level framework. A dividing mechanism with boundary conditions is employed in top-level simulation to divide the global event list into small sizes. A timing-focuses strategy based on max-plus algebra is applied in bottom-level local simulation to further reduce local event lists. With this new method it is possible to mimic real production systems fast and accurately within a reasonable computational time frame. The effectiveness and efficiency of the new simulation method are validated through experimental results.

Modeling of multi-agent system for power system topology verification with use of Petri nets

Abstract: A correct power network topology model is essential from viewpoint of various dispatching control applications. This model is created with use of states of switching devices which are gathered in real-time. In some circumstances, there can be errors in the obtained power network connectivity model. The paper deals with the verification of the mentioned model with the use of a multi-agent system. A multi-agent system can be considered as a discrete event dynamic system. In this situation, to assess structural properties of the multi-agent system for topology verification, Petri nets can be utilized. The aim of the paper is to show rules of modeling and analyzing the considered multi-agent system with use of Petri nets.

IDENTIFICATION OF DISCRETE EVENT SYSTEMS - Implementation Issues and Model Completeness

Abstract: This paper presents some practical issues for the identification of discrete event systems (DES). The considered class of systems consists of a plant and a controller running is a closed-loop. Special emphasis is given to a data collection procedure using industrial controllers and its impact on the external DES-behavior of the considered systems. For models identified on the basis of observed external DES behavior using the algorithm from (Klein, 2005) it is shown that under some conditions, the identified model language simulates the complete original system language even if only a subset of this language is available for identification. This model characteristic is crucial for many model-based techniques like diagnosis or verification. Analyzing the observed data of a laboratory facility it is shown how it can be decided if the conditions for a complete model hold for an existing application.

Constraint-based modeling of discrete event dynamic systems

Abstract: Numerous frameworks dedicated to the modeling of discrete event dynamic systems have been proposed to deal with programming, simulation, validation, situation tracking, or decision tasks: automata, Petri nets, Markov chains, synchronous languages, temporal logics, event and situation calculi, STRIPS…All these frameworks present significant similarities, but none offers the flexibility of more generic frameworks such as logic or constraints. In this article, we propose a generic constraint-based framework for the modeling of discrete event dynamic systems, whose basic components are state, event, and time attributes, as well as constraints on these attributes, and which we refer to as CNT for Constraint Network on Timelines. The main strength of such a framework is that it allows any kind of constraint to be defined on state, event, and time attributes. Moreover, its great flexibility allows it to subsume existing apparently different frameworks such as automata, timed automata, Petri nets, and classical frameworks used in planning and scheduling.

Activity regions for the specification of discrete event systems

Abstract: The common view on modeling and simulation of dynamic systems is to focus on the specification of the state of the system and its transition function. Although some interesting challenges remain to efficiently and elegantly support this view, we consider in this paper that this problem is solved. Instead, we propose here to focus on a new point of view on dynamic system specifications: the activity exhibited by their discrete event simulation. We believe that such a viewpoint introduces a new way for analyzing, modeling and simulating systems. We first start with the definition of the key notion of activity for the specification of a specific class of dynamic system, namely discrete event systems. Then, we refine this notion to characterize activity regions in time, in space, in states and in hierarchical component-based models. Examples are given to illustrate and stress the importance of this notion.

Aircraft Taxi Route Planning for A-SMGCS Based on Discrete Event Dynamic System modeling

Abstract: To implement taxi route planning for aircrafts in Advanced Surface Movement Guidance and Control System (A-SMGCS), discrete event dynamic system (DEDS) modeling method is adopted. The surface movement model based on Petri Nets is proposed taking into account the runway, taxiways and apron running regulations. The surface movement controlling regulations are defined and the conflict detection and resolution is transformed into the state forbidden problem. To describe dynamic behaviors of aircraft surface movement model, the enabling, firing rule and the staying time window are defined. The dynamic route is optimized from static admissible routes. The result of planning indicates that dynamic route planned can decrease the potential conflicts, reduce waiting time of aircrafts and increase the capacity of airport.

Non‐blocking decentralized control of discrete event systems based on Petri nets

Abstract: The non-blocking property of discrete event systems can formulate many practical and important properties of manufacturing systems, such as deadlock freeness, liveness and reversibility. But it is difficult to guarantee non-blocking control. This paper presents a hybrid approach to decentralized control of discrete event systems. More generalized constraints are considered in this approach, which gives a graphical way of designing coordinators to keep the non-blocking property of the closed-loop system with decentralized supervisors. This approach also guarantees that the closed-loop system is maximally permissive. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

SetExp: a method of transformation of timed automata into finite state automata

Abstract: Real-time discrete event systems are discrete event systems with timing constraints, and can be modeled by timed automata. The latter are convenient for modeling real-time discrete event systems. However, due to their infinite state space, timed automata are not suitable for studying real-time discrete event systems. On the other hand, finite state automata, as the name suggests, are convenient for modeling and studying non-real time discrete event systems. To take into account the advantages of finite state automata, an approach for studying real-time discrete event systems is to transform, by abstraction, the timed automata modeling them into finite state automata which describe the same behaviors. Then, studies are performed on the finite state automata model by adapting methods designed for non real-time discrete event systems. In this paper, we present a method for transforming timed automata into special finite state automata called Set-Exp automata. The method, called SetExp, models the passing of time as real events in two types: Set events which correspond to resets with programming of clocks, and Exp events which correspond to the expiration of clocks. These events allow to express the timing constraints as events order constraints. SetExp limits the state space explosion problem in comparison to other transformation methods of timed automata, notably when the magnitude of the constants used to express the timing constraints are high. Moreover, SetExp is suitable, for example, in supervisory control and conformance testing of real-time discrete event systems.

Stochastic Graph Transformation with Regions

Abstract: Graph transformation can be used to implement stochastic simulation of dynamic systems based on semi-Markov processes, extending the standard approach based on Markov chains. The result is a discrete event system, where states are graphs, and events are rule matches associated to general distributions, rather than just exponential ones. We present an extension of this model, by introducing a hierarchical notion of event location, allowing for stochastic dependence of higher- level events on lower-level ones.

Continuous and discrete time models

Abstract: Most economists recognize that the use of discrete time is only an approximation, but assume (usually implicitly) that the error of approximation involved is trivially small relative to the other sorts of simplification and approximation inherent in economic theorizing. We consider below first the conditions under which this convenient assumption may be seriously misleading. We discuss briefly how to proceed when the assumption fails, and the state of continuous time economic theory.

Quantifying Heuristics in the Ordinal Optimization Framework

Abstract: Finding the optimal design for a discrete event dynamic system (DEDS) is in general difficult due to the large search space and the simulation-based performance evaluation. Various heuristics have been developed to find good designs. An important question is how to quantify the goodness of the heuristic designs. Inspired by the Ordinal Optimization, which has become an important tool for optimizing DEDS, we provide a method which can quantify the goodness of the design. By comparing with a set of designs that are uniformly sampled, we measure the ordinal performances of heuristic designs, i.e., we quantify the ranks of all (or some of) the heuristic designs among all the designs in the entire search space. The mathematical tool we use is the Hypothesis Testing, and the probability of making Type II error in the quantification is controlled to be under a very low level. The method can be used both when the performances of the designs can be accurately evaluated and when such performances are estimated by a crude but computationally easy model. The method can quantify both heuristics that output a single design and that output a set of designs. The method is demonstrated through numerical examples.

Language-based minimization of sensor activation for event diagnosis

Abstract: The problem of dynamic sensor activation for event diagnosis in discrete event systems is considered. Diagnostic agents are able to activate/deactivate sensors dynamically during the operation of the system. Sensor activation policies are functions that determine which sensors are on after a system trajectory. The sensor activation policy must be sufficient to fulfill the diagnosis duty. To compute minimal policies, in previous work, we propose language partition methods to restrict the solution space to be finite. In this paper, we present an algorithm that can be used to compute a provable minimal sensor activation policy without such a restriction. The output of our algorithm, which is a deterministic finite-state automaton, can be directly used to control sensors and diagnose the system.

A framework of fuzzy hybrid systems for modelling and control

Abstract: This paper presents a new approach to modelling and control of hybrid systems with both continuous variables and discrete events. Applying the fuzzy set theory, a hierarchical fuzzy hybrid structure consisting of a fuzzy discrete event dynamic system and a continuous variable dynamic system is constructed, which not only captures the hybrid continuous/discrete dynamics but also handles the uncertainties in states and state transitions. The identification of continuous and discrete components is developed, and the hybrid control is then synthesised by fuzzy IF–THEN rules embedded in the fuzzy interface. An example of the optimisation of a production line in manufacturing shows the efficacy of the proposed approach.

Parallel Discrete Event Simulation

Abstract: Ever since discrete event simulation has been adopted by a large research community, simulation developers have attempted to draw benefits from executing a simulation on multiple processing units in parallel. Hence, a wide range of research has been conducted on Parallel Discrete Event Simulation (PDES). In this chapter we give an overview of the challenges and approaches of parallel simulation. Furthermore, we present a survey of the parallelization capabilities of the network simulators OMNeT++, ns-2, DSIM and JiST.

Efficient Simulation Algorithms for Optimization of Discrete Event Systems Based on Measure-Valued Differentiation

Abstract: A wide range of stochastic systems in the area of manufacturing, transportation, finance, logistics and communication can be modeled as discrete event systems (DES). In general, however, " real world " DESs either do not conform to some assumptions we made in order to obtain a solution, or they are just too complex to yield analytical solutions. In such cases, simulation becomes a very attractive tool for performance evaluation and optimization of DESs. Consequently, the derivatives of the performance measures have to be estimated, which leads to the problem of finding efficient unbiased gradient estimators. From a practical point of view, gradient estimators should, 1) be easy to implement, 2) have low variance and 3) have a low computational effort. This thesis is devoted to developing efficient gradient estimation methods for optimization of DESs and to applying these resulting algorithms to real-life problems. include gradient estimation, optimization and control of discrete event systems, and performance evaluation.

Graph transformation for domain-specific discrete event time simulation

Abstract: Graph transformation is being increasingly used to express the semantics of domain specific visual languages since its graphical nature makes rules intuitive However, many application domains require an explicit handling of time in order to represent accurately the behaviour of the real system and to obtain useful simulation metrics Inspired by the vast knowledge and experience accumulated by the discrete event simulation community, we propose a novel way of adding explicit time to graph transformation rules In particular, we take the event scheduling discrete simulation world view and incorporate to the rules the ability of scheduling the occurrence of other rules in the future Hence, our work combines standard, efficient techniques for discrete event simulation (based on the handling of a future event set) and the intuitive, visual nature of graph transformation Moreover, we show how our formalism can be used to give semantics to other timed approaches

Supervisor direct synthesis method for a structured discrete dynamical system

Abstract: We present an implementation method for a supervisor of a discrete event system (DES) structured in a special way. Such a DES has the following characteristic features: the language generator is represented by a set of finite automata, the language model is extended with a new type of events called "expected," and the specification is defined as a sequence of control commands. The primary advantage of our method is that it uses structural knowledge of the event stream in order to construct a supervisor. Thus, we achieve linear dependence of the supervisor's size in the input data.

Discrete models of physicochemical processes and their parallel implementation

Abstract: Discrete simulation method of physicochemical kinetic processes is proposed and investigated. The method is based on formal representation of classical Von-Neumann's Cellular Automaton (CA) extension, which allow all kind of discrete alphabets, probabilistic transition functions, and asynchronous mode of operation. Some techniques for simple CA composition are given for simulating complex processes. Transformation of asynchronous CA into block-synchronous type is used to provide high efficiency of parallel implementation.

Research on network security real-time risk assessment model

Abstract: Information Security Risk Assessment is a means of providing decision-makers with information needed to understand the vulnerabilities and threats factors that can negatively influence operations and outcomes and make informed judgments concerning the extent of actions needed to reduce risk. The first is to improve the parameter learning algorithm of CTHMMs. We compare it to the previous using the following indicators: pattern recognition and error rate as well as algorithm complexity. Improved algorithm is a contribution to the Markov theory. Stochastic statistical model pertain to discrete event dynamic system has recently become a familiar tool in computer and network security research. The importance and significance is difficult to express with ordinary glossary.

Research of MRAC on intervals between arriving flights controlling

Abstract: In this paper, the problem of interval controlling between arriving flights is researched. According to character of arriving flights dynamic process, bring forward reasonable assumption, and convert problem of arriving flights' interval controlling, whose attribute is discrete event dynamic system, into problem of generalized dynamic system controlling. Through analyzing actual measuring data, establish model of arriving flights dynamic process by identification technology, and design arriving flights interval control system with method of model reference adaptive control (MRAC). Adopting MATLAB to carry out simulation, result shows that arriving flights' intervals variance obviously reduces and process of arriving flights becomes smooth. This supplies new way to research and develop air traffic control (ATC) assistant decision system, and realize ATC automation.

Robust invariance in uncertain discrete event systems with applications to transportation networks

Abstract: This paper studies a class of uncertain discrete event systems over the max-plus algebra, where system matrices are unknown but are convex combinations of known matrices. These systems model a wide range of applications, for example, transportation systems with varying vehicle travel time and queueing networks with uncertain arrival and queuing time. This paper presents computational methods for different robust invariant sets of such systems. A recursive algorithm is given to compute the supremal robust invariant sub-semimodule in a given sub-semimodule. The algorithm converges to a fixed point in a finite number of iterations under proper assumptions on the state semimodule. This paper also presents computational methods for positively robust invariant polyhedral sets. A search algorithm is presented for the positively robust invariant polyhedral sets. The main results are applied to the time table design of a public transportation network.

Dynamic information theory and information description of dynamic systems

Abstract: In this paper, we develop dynamic statistical information theory established by the author. Starting from the ideas that the state variable evolution equations of stochastic dynamic systems, classical and quantum nonequilibrium statistical physical systems and special electromagnetic field systems can be regarded as their information symbol evolution equations and the definitions of dynamic information and dynamic entropy, we derive the evolution equations of dynamic information and dynamic entropy that describe the evolution laws of dynamic information. These four kinds of evolution equations are of the same mathematical type. They show in unison when information transmits in coordinate space outside the systems that the time rate of change of dynamic information densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes, and that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes. When space noise can be neglected, an information wave will appear. If we only consider the information change inside the systems, dynamic information evolution equations reduce to information equations corresponding to the dynamic equations which describe evolution laws of the above dynamic systems. This reveals that the evolution laws of respective dynamic systems can be described by information equations in a unified fashion. Hence, the evolution processes of these dynamic systems can be abstracted as the evolution processes of information. Furthermore, we present the formulas for information flow, information dissipation rate, and entropy production rate. We prove that the information production probably emerges in a dynamic system with internal attractive interaction between the elements, and derive a formula for this information production rate. Thereby, we obtain an expression for the time rate of total information change of a dynamic system, which is equal to the algebraic sum of the formulas for information dissipation rate, information production rate and information inflow rate, and which exhibits a unified information description for the evolution including degradation and self-organizing evolution of dynamic systems.

Decentralized diagnosis of discrete event systems modeled by Mealy automata with nondeterministic output functions

Abstract: In the conventional framework for failure diagnosis of partially observed discrete event systems, it is assumed that, for each event, the corresponding output symbol is determined uniquely. However, this assumption does not hold in discrete event systems such as a mobile system, where an output symbol depends on not only an event but also a state at which the event occurs. In this paper, we model such discrete event systems by Mealy automata with nondeterministic output functions, and consider a decentralized failure diagnosis problem that requires any occurrence of a failure should be detected by at least one local diagnoser within a uniformly bounded number of steps. We present a necessary and sufficient condition for the existence of a decentralized diagnoser. We then present an algorithm for verifying this condition. Moreover, we present a method for synthesizing local online diagnosers.

Fault accommodation in discrete - event systems

Abstract: The problem of fault accommodation in discrete-event systems is considered. Solution of the problem is related to constructing the control law which provides full decoupling with respect to fault effects. Existing conditions are formulated and calculating relations are given for the control law determination.

Stability problem for a predator-prey system

Abstract: This paper considers the growth rate dynamics of a predator-prey system as a discrete event dynamical system Timed Petri nets are a graphical and mathematical modeling tool applicable to discrete event systems in order to represent its states evolution Lyapunov stability theory provides the required tools needed to aboard the stability problem for the predator-prey system treated as a discrete event system modeled with timed petri nets By proving boundedness one confirms a dominant oscillating behavior of both populations dynamics performance However, the oscillating frequency results to be unknown This inconvenience is overcome by considering a specific recurrence equation, in the max-plus algebra.

Air combat game and simulation

Abstract: The air combat process is regarded as the discrete event dynamic system which is composed of a series of discrete-states, and its discrete state sub-model is established. In order to choose the tactical maneuver, the evaluation function is constructed by the air combat situation index and the air combat capability index. Combining with the 3 degree-of-freedom (3DOF) aircraft model, the maneuver command generator is designed, controlling the moving state of aircraft. Finally, the simulation of the combat-turning is carried out using Matlab.

Analysis of Linear Time-Invariant Discrete System Operating under the State Feedback Control with Observer

Abstract: In the modern automatic systems,the technique of "on-line identification and operation by digital computing" is applied widely.Therefore the discrete systems are more emphasized in comparison with the continuous system.And some fundamental concepts,analysis and synthesis introduced in the continuous system reappear here in many respects.The paper would study the different point between the discrete system and the continuous one,such as controllability,pole-assignment,observer and etc.At last an example is given for application,and the method may also be extended to "Robust regulator design".

Research on the simulation problem of support vehicle requirement among the Multi-Aircraft Flight Support Process

Abstract: Among the Multi-Aircraft Flight Support Process, as it refers to much influence factors for determining the requirement of the support vehicles, and the process of vehicle scheduling is complicated and changeful, so it is difficult to establish the analytic model for the above-mentioned NP hard problem. But the simulation model about the process of support vehicle scheduling could be found by making use of the discrete event dynamic system's modeling and simulation technology, through setting the different kinds of aircraft' flight batch interval in the simulation software Arena, Simulates the flight support process. Until the output of simulation which satisfies the requirement of flight ready model is obtained by continually adjusting the number of different kinds of support vehicle, whose scheduled utilization rate is higher than the other support vehicle in the software's process analyzer tool. The simulation result shows that the proposed method provides a new way to deal with the requirement problem of Multi-Aircraft flight support vehicles.