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Approx. 484 pages
This book shows how supervisory control theory (SCT) supports the formulation of various control problems of standard types, like the synthesis of controlled dynamic invariants by state feedback, and the resolution of such problems in terms of naturally definable control-theoretic concepts and properties, like reachability, controllability and observability. It exploits a simple, abstract model of controlled discrete-event systems (DES) that has proved to be tractable, appealing to control specialists, and expressive of a range of control-theoretic ideas. It allows readers to choose between automaton-based and dually language-based forms of SCT, depending on whether their preference is for an internal-structural or external-behavioral description of the problem. The monograph begins with two chapters on algebraic and linguistic preliminaries and the fundamental concepts and results of SCT are introduced. To handle complexity caused by system scale, architectural approaches—the horizontal modularity of decentralized and distributed supervision and the vertical modularity of hierarchical supervision—are introduced. Supervisory control under partial observation and state-based supervisory control are also addressed; in the latter, a vector DES model that exploits internal regularity of algebraic structure is proposed. Finally SCT is generalized to deal with timed DES by incorporating temporal features in addition to logical ones. Researchers and graduate students working with the control of discrete-event systems or who are interested in the development of supervisory control methods will find this book an invaluable aid in their studies. The text will also be of assistance to researchers in manufacturing, logistics, communications and transportation, areas which provide plentiful examples of the class of systems being discussed.
Discrete Event Systems: Diagnosis and Diagnosability addresses the problem of fault diagnosis of Discrete Event Systems (DESs). This book provides the basic techniques and approaches necessary for the design of an efficient fault diagnosis system for a wide range of modern engineering applications. This book classifies the different techniques and approaches according to several criteria such as: modeling tools (Automata, Petri nets, Templates) that is used to construct the model; the information (qualitative based on events occurrences and/or states outputs, quantitative based on signal processing, data analysis) that is needed to analyze and achieve the diagnosis; the decision structure (centralized, decentralized) that is required to achieve the diagnosis; as well as the complexity (polynomial, exponential) of the algorithm that is used to determine the set of faults that the proposed approach is able to diagnose as well as the delay time required for this diagnosis. The goal of this classification is to select the efficient method to achieve the fault diagnosis according to the application constraints. This book will include illustrated examples of the presented methods and techniques as well as a discussion on the application of these methods on several real-world problems.
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.
This work presents a novel approach to modeling, analysis and diagnosis of coupled mechatronical systems with partially autonomous behavior and asynchronous state transitions. The systems under consideration are assumed to have the following properties: The internal interactions are immeasurable but reliable and the measurements relevant for diagnosis are given as a sequence of events. Asynchronous networks of input/output automata (I/O-automata) are developed to cope with partial coupling between components and to reduce the computational complexity of the diagnostic algorithms. I/O-automata are used to model those components. Their measurable inputs and outputs are modeled as control signals. Interconnection signals are used to model the internal dependencies among the components. They are linked via an interaction block to one another. The criterion known from synchronous networks of I/O-automata is extended to ensure the well-posedness of this modeling formalism. To check for partially autonomous behavior, two types of autonomy are introduced and discussed: Structural autonomy and state-dependent autonomy. To carry out the diagnosis, three different information structures are investigated: Centralized, decentralized and partially coordinated. The centralized approach yields the ideal diagnostic result, but reduction of the computational complexity by using online composition is rather small. Further reduction of the computational complexity is accomplished by decentralized diagnosis. It yields only in the case of state-dependent autonomy a complete and sound diagnostic result. In general, the lack of soundness arises. Both, obtaining an ideal diagnostic result and reducing the computational complexity, is obtained by the partially coordinated diagnostic algorithm.
In recent years, there has been a growing debate, particularly in the UK and Europe, over the merits of using discrete-event simulation (DES) and system dynamics (SD); there are now instances where both methodologies were employed on the same problem. This book details each method, comparing each in terms of both theory and their application to various problem situations. It also provides a seamless treatment of various topics--theory, philosophy, detailed mechanics, practical implementation--providing a systematic treatment of the methodologies of DES and SD, which previously have been treated separately.
Energy consumption is of great interest to manufacturing companies. Beyond considering individual processes and machines, the perspective on process chains and factories as a whole holds major potentials for energy efficiency improvements. To exploit these potentials, dynamic interactions of different processes as well as auxiliary equipment (e.g. compressed air generation) need to be taken into account. In addition, planning and controlling manufacturing systems require balancing technical, economic and environmental objectives. Therefore, an innovative and comprehensive methodology – with a generic energy flow-oriented manufacturing simulation environment as a core element – is developed and embedded into a step-by-step application cycle. The concept is applied in its entirety to a wide range of case studies such as aluminium die casting, weaving mills, and printed circuit board assembly in order to demonstrate the broad applicability and the benefits that can be achieved.
Computer modeling and simulation (M&S) allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems. Based on over 20 years of evolution within a classroom environment, as well as on decades-long experience in developing simulation-based solutions for high-tech industries, Modeling and Simulation of Discrete-Event Systems is the only book on DES-M&S in which all the major DES modeling formalisms – activity-based, process-oriented, state-based, and event-based – are covered in a unified manner: A well-defined procedure for building a formal model in the form of event graph, ACD, or state graph Diverse types of modeling templates and examples that can be used as building blocks for a complex, real-life model A systematic, easy-to-follow procedure combined with sample C# codes for developing simulators in various modeling formalisms Simple tutorials as well as sample model files for using popular off-the-shelf simulators such as SIGMA®, ACE®, and Arena® Up-to-date research results as well as research issues and directions in DES-M&S Modeling and Simulation of Discrete-Event Systems is an ideal textbook for undergraduate and graduate students of simulation/industrial engineering and computer science, as well as for simulation practitioners and researchers.
The two-volume set LNCS 3644 and LNCS 3645 constitutes the refereed proceedings of the International Conference on Intelligent Computing, ICIC 2005, held in Hefei, China, in August 2005. The program committee selected 215 carefully revised full papers for presentation in two volumes from over 2000 submissions, based on rigorous peer reviews. The first volume includes all the contributions related with perceptual and pattern recognition, informatics theories and applications computational neuroscience and bioscience, models and methods, and learning systems. The second volume collects the papers related with genomics and proteomics, adaptation and decision making, applications and hardware, and other applications.
This thesis deals with active fault-tolerant control of discrete event systems modeled by deterministic Input/Output (I/O) automata. Active fault-tolerant control realizes three operating modes - nominal control, fault diagnosis and controller reconfiguration. A new fault-tolerant controller which autonomously ensures the fulfillment of the control aim, both, in the faultless and the faulty case is developed. The control aim is to steer the plant into a desired final state while guaranteeing the avoidance of illegal transitions. Corresponding to the three operating modes, the proposed integrated fault-tolerant controller consists of a tracking controller, a diagnostic unit and a reconfiguration unit. As long as no fault is present, the tracking controller controls the plant in a feedback loop in order to guarantee the fulfillment of the control aim. At the same time the diagnostic unit detects whether a fault occurred. If a fault is detected, a novel active diagnosis method is used in order to identify the present fault as well as the current state of the faulty plant. The reconfiguration unit uses the diagnostic result provided by the diagnostic unit to reconfigure the tracking controller. As a main result, it is proved that the plant in the fault-tolerant control loop fulfills the control aim in the faultless as well as in the faulty case if the control loop is recoverable. The applicability of the fault-tolerant control method is demonstrated by means of a handling process at the Handling System HANS.