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Introduction to Discrete Event Systems

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ISBN-10: 0387333320

ISBN-13: 9780387333328

Edition: 2nd 2008

Authors: Christos G. Cassandras, St�phane Lafortune

List price: $149.99
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Description:

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…    
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Book details

List price: $149.99
Edition: 2nd
Copyright year: 2008
Publisher: Springer
Publication date: 12/14/2009
Binding: Hardcover
Pages: 772
Size: 7.25" wide x 10.25" long x 1.75" tall
Weight: 3.828
Language: English

Christos G. Cassandras is Professor of Manufacturing Engineering and Professor of Electrical and Computer Engineering at Boston University. He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, stochastic optimization, and computer simulation, with applications to computer and sensor networks,…    

Christos G. Cassandras is Professor of Manufacturing Engineering and Professor of Electrical and Computer Engineering at Boston University. He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, stochastic optimization, and computer simulation, with applications to computer and sensor networks,…    

Preface - Second Edition
Preface
Organization of Book
Systems and Models
Introduction
System and Control Basics
The Concept of System
The Input-Output Modeling Process
The Concept of State
The State Space Modeling Process
Sample Paths of Dynamic Systems
State Spaces
The Concept of Control
The Concept of Feedback
Discrete-Time Systems
Discrete Event Systems
The Concept of Event
Characteristic Properties of Discrete Event Systems
The Three Levels of Abstraction in the Study of Discrete Event Systems
Examples of Discrete Event Systems
Hybrid Systems
Summary Of System Classifications
The Goals Of System Theory
Summary
Problems
Selected References
Languages and Automata
Introduction
The Concepts of Languages and Automata
Language Models of Discrete-Event Systems
Automata
Languages Represented by Automata
Nondeterministic Automata
Automata with Inputs and Outputs
Operations on Automata
Unary Operations
Composition Operations
State Space Refinement
Observer Automata
Equivalence of Automata
Finite-State Automata
Definition and Properties of Regular Languages
Regular Expressions
State Space Minimization
Analysis Of Discrete-Event Systems
Safety and Blocking Properties
Partially-Observed DES
Event Diagnosis
Software Tools and Computational Complexity Issues
Formal Verification and Model Checking
Summary
Problems
Selected References
Supervisory Control
Introduction
Feedback Control with Supervisors
Controlled Discrete Event Systems
Control Under Partial Observation
Specifications on Controlled System
Modeling of Specifications as Automata
The Need for Formal Methods
Control with Partial Controllability
Controllability Theorem
Realization of Supervisors
The Property of Controllability
Some Supervisory Control Problems and Their Solutions
Computation of <$>K^{\uparrow C}<$>: Prefix-Closed Case
Computation of <$>K^{\downarrow C}<$>
Nonblocking Control
Nonblocking Controllability Theorem
Nonblocking Supervisory Control
Computation of <$>K^{\uparrow C}<$>: General Case
Dealing with Blocking Supervisors
Control with Modular Specifications
Control Under Partial Observation
Controllability and Observability Theorem
Realization of P-Supervisors
The Property of Observability
Supervisory Control Problems Under Partial Observation
The Property of Normality
Decentralized Control
Conjunctive Architecture
Disjunctive Architecture
Combined Architecture
Realization of Decentralized Supervisors
The Property of Coobservability
Undecidability in Decentralized Control
Summary
Problems
Selected References
Petri Nets
Introduction
Petri Net Basics
Petri Net Notation and Definitions
Petri Net Markings and State Spaces
Petri Net Dynamics
Petri Net Languages
Petri Net Models for Queueing Systems
Comparison of Petri Nets and Automata
Analysis Of Petri Nets
Problem Classification
The Coverability Tree
Applications of the Coverability Tree
Linear-Algebraic Techniques
Control of Petri Nets
Petri Nets and Supervisory Control Theory
State-Based Control of Petri Nets
Summary
Problems
Selected References
Timed and Hybrid Models
Introduction
Timed Automata
The Clock Structure
Event Timing Dynamics
A State Space Model
Queueing Systems as Timed Automata
The Event Scheduling Scheme
Timed Petri Nets
Timed Petri Net Dynamics
Queueing Systems as Timed Petri Nets
Dioid Algebras
Basic Properties of the (max, +) Algebra
Modeling Queueing Systems in the (max, +) Algebra
Alternative Timed Models
Timed Automata with Guards
Model Definition
Model Execution
Parallel Composition
Untiming
Hybrid Models
Hybrid Automata
Summary
Problems
Selected References
Stochastic Timed Automata
Introduction
Stochastic Process Basics
Continuous-state and Discrete-state Stochastic Processes
Continuous-time and Discrete-time Stochastic Processes
Some Important Classes of Stochastic Processes
Stochastic Clock Structures
Stochastic Timed Automata
The Generalized Semi-Markov Process
Queueing Systems as Stochastic Timed Automata
GSMP Analysis
The Poisson Counting Process
Properties of the Poisson Process
Exponentially Distributed Interevent Times
The Memoryless Property
Superposition of Poisson Processes
The Residual Lifetime Paradox
Automata with Poisson Clock Structure
Distribution of Interevent Times
Distribution of Events
Markov Chains
Extensions of the GSMP
Summary
Problems
Selected References
Markov Chains
Introduction
Discrete-Time Markov Chains
Model Specification
Transition Probabilities and the Chapman-Kolmogorov Equations
Homogeneous Markov Chains
The Transition Probability Matrix
State Holding Times
State Probabilities
Transient Analysis
Classification of States
Steady State Analysis
Irreducible Markov Chains
Reducible Markov Chains
Continuous-Time Markov Chains
Model Specification
Transition Functions
The Transition Rate Matrix
Homogeneous Markov Chains
State Holding Times
Physical Interpretation and Properties of the Transition Rate Matrix
Transition Probabilities
State Probabilities
Transient Analysis
Steady State Analysis
Birth-Death Chains
The Pure Birth Chain
The Poisson Process Revisited
Steady State Analysis of Birth-Death Chains
Uniformization of Markov Chains
Summary
Problems
Selected References
Introduction to Queueing Theory
Introduction
Specification of Queueing Models
Stochastic Models for Arrival and Service Processes
Structural Parameters
Operating Policies
The A/B/m/K Notation
Open and Closed Queueing Systems
Performance of A Queueing System
Queueing System Dynamics
Little's Law
Simple Markovian Queueing Systems
The M/M/1 Queueing System
The M/M/m Queueing System
The M/M/&#8734; Queueing System
The M/M/1/K Queueing System
The M/M/m/m Queueing System
The M/M/1//N Queueing System
The M/M/m/K/N Queueing System
Markovian Queueing Networks
The Departure Process of the M/M/1 Queueing System
Open Queueing Networks
Closed Queueing Networks
Product Form Networks
Non-Markovian Queueing Systems
The Method of Stages
Mean Value Analysis of the M/G/1 Queueing System
Software Tools for the Analysis of General Queueing Networks
Summary
Problems
Selected References
Controlled Markov Chains
Introduction
Applying ""Control"" in Markov Chains
Markov Decision Processes
Cost Criteria
Uniformization
The Basic Markov Decision Problem
Solving Markov Decision Problems
The Basic Idea of Dynamic Programming
Dynamic Programming and the Optimality Equation
Extensions to Unbounded and Undiscounted Costs
Optimization of the Average Cost Criterion
Control of Queueing Systems
The Admission Problem
The Routing Problem
The Scheduling Problem
Summary
Problems
Selected References
Introduction to Discrete-Event Simulation
Introduction
The Event Scheduling Scheme
Simulation of a Simple Queueing System
The Process-Oriented Simulation Scheme
Discrete-Event Simulation Languages
Random Number Generation
The Linear Congruential Technique
Random Variate Generation
The Inverse Transform Technique
The Convolution Technique
The Composition Technique
The Acceptance-Rejection Technique
Output Analysis
Simulation Characterizations
Parameter Estimation
Output Analysis of Terminating Simulations
Output Analysis of Non-Terminating Simulations
Summary
Problems
Selected References
Sensitivity Analysis and Concurrent Estimation
Introduction
Sample Functions and their Derivatives
Performance Sensitivities
The Uses of Sensitivity Information
Perturbation Analysis: Some Key Ideas
PA of GI/G/1 Queueing Systems
Perturbation Generation
Perturbation Propagation
Infinitesimal Perturbation Analysis (IPA)
Implementation of IPA for the GI/G/1System
IPA for Stochastic Timed Automata
Event Time Derivatives
Sample Function Derivatives
Performance Measure Derivatives
IPA Applications
Sensitivity Estimation Revisited
Extensions of IPA
Discontinuities due to Multiple Customer Classes
Discontinuities due to Routing Decisions
Discontinuities due to Blocking: IPA with Event Rescheduling (RIPA)
Smoothed Perturbation Analysis (SPA)
Systems with Real-Time Constraints
Marking and Phantomizing Techniques
IPA for Stochastic Hybrid Automata
Stochastic Fluid Models (SFMs)
Sample paths of SFMs
Comparing SFMs to Their DES Counterparts
IPA for a Single-Class Single-Node SFM
IPA for SFMs with Multiple Classes, Multiple Nodes and Feedback
PA for Finite Parameter Changes
Concurrent Estimation
The Sample Path Constructability Problem
Uses of Concurrent Estimation: ""Rapid Learning""
Sample Path Constructability Conditions
The Standard Clock Approach
Augmented System Analysis
The ""Time Warping"" Algorithm
Summary
Problems
Selected References
Review of Probability Theory
Basic Concepts and Definitions
Conditional Probability
Random Variables
Conditional Distributions
Functions of Random Variables
Expectation
Characteristic Functions
Random Sequences and Random Processes
IPA Estimator
Index
About the Authors