Książki

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.

Introduction to Discrete Event Systems

Preface - Second Edition.- Preface.- 1 Systems and Models: Introduction.- System and Control Basics.- Discrete Event Systems.- Summary of System Classifications.- The Goals of System Theory.- Summary.- Problems.- Selected References.- 2 Languages and Automata: Introduction.- The Concepts of Languages and Automata.- Operations on Automata.- Finite-State Automata.- Analysis of Discrete-Event Systems.- Summary.- Problems.- Selected References.- 3 Supervisory Control: Introduction.- Feedback Control with Supervisors.- Specifications on Controlled System.- Control with Partial Controllability.- Nonblocking Control.- Control with Modular Specifications.- Control Under Partial Observation.- Decentralized Control.- Summary.- Problems.- Selected References.- 4 Petri Nets: Introduction.- Petri Net Basics.- Comparison of Petri Nets and Automata.- Analysis of Petri Nets.- Control of Petri Nets.- Summary.- Problems.- Selected References.- 5 Timed and Hybrid Models: Introduction.- Timed Automata.- Timed Petri Nets.- Dioid Algebras.- Alternative Timed Models.- Timed Automata with Guards.- Hybrid Models.- Summary.- Problems.- Selected References.- 6 Stochastic Timed Automata: Introduction.- Stochastic Process Basics.- Stochastic Clock Structures.- Stochastic Timed Automata.- The Generalized Semi-Markov Process.- The Poisson Counting Process.- Properties of the Poisson Process.- Automata with Poisson Clock Structure.- Extensions of the GSMP.- Summary.- Problems.- Selected References.- 7 Markov Chains: Introduction.- Discrete-Time Markov Chains.- Continuous-Time Markov Chains.- Birth-Death Chains.- Uniformization of Markov Chains.- Summary.-Problems.- Selected References.- 8 Introduction to Queueing Theory: Introduction.- Specification of Queueing Models.- Performance of a Queueing System.- Queueing System Dynamics.- Little's Law.- Simple Markovian Queueing Systems.- Markovian Queueing Networks.- Non-Markovian Queueing Systems.- Summary.- Problems.- Selected References.- 9 Controlled Markov Chains: Introduction.- Applying 'Control' in Markov Chains.- Markov Decision Processes.- Solving Markov Decision Problems.- Control of Queueing Systems.- Summary.- Problems.- Selected References.- 10 Introduction to Discrete-Event Simulation: Introduction.- The Event Scheduling Scheme.- The Process-Oriented Simulation Scheme.- Discrete-Event Simulation Languages.- Random Number Generation.- Random Variate Generation.- Output Analysis.- Summary.- Problems.- Selected References.- 11 Sensitivity Analysis and Concurrent Estimation: Introduction.- Sample Functions and Their Derivatives.- Perturbation Analysis: Some Key Ideas.- PA of GI/G/1 Queueing Systems.- IPA for Stochastic Timed Automata.- Sensitivity Estimation Revisited.- Extensions of IPA.- Smoothed Perturbation Analysis (SPA).- IPA for Stochastic Hybrid Automata.- PA for Finite Parameter Changes.- Concurrent Estimation.- Summary.- Problems.- Selected References.- I: 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.- II: IPA Estimator.- Index.- About the Authors.