MULTIAGENT SYSTEMS : introduction and coordination control.

Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel appro...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Mahmoud, Magdi S.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Place of publication not identified] CRC Press, 2020.
Temas:
Multiagent systems.
Systèmes multiagents (Intelligence artificielle)
COMPUTERS > Database Management > Data Mining.
COMPUTERS > Programming > Systems Analysis & Design.
COMPUTERS > Data Modeling & Design.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright Page
  • Dedication
  • Preface
  • Acknowledgement
  • Table of Contents
  • Author Biography
  • 1: Introduction
  • 1.1 Overview
  • 1.2 Elements of Graph Theory
  • 1.2.1 Basic Results
  • 1.2.2 Laplacian Spectrum of Graphs
  • 1.2.3 Properties of Adjacency Matrix
  • 1.2.4 Nonlinear Stochastic Dynamical Systems
  • 1.2.5 Complex Dynamical Systems
  • 1.2.6 Delay Effects
  • 1.2.7 Sampled-Data Framework
  • 1.3 Multiagent System Approach
  • 1.3.1 Practical Examples
  • 1.3.2 Some Relevant Definitions
  • 1.4 Mathematical Models for Agent Dynamics
  • 1.4.1 Single Integrator Model
  • 1.4.2 Double Integrator Model
  • 1.4.3 Uncertain Fully Actuated Model
  • 1.4.4 Non-Holonomic Unicycle Model
  • 1.5 Coordination and Control Problems
  • 1.5.1 Aggregation and Social Foraging
  • 1.5.2 Flocking and Rendezvous
  • 1.5.3 Synchronization of Coupled Nonlinear Oscillators
  • 1.6 Scope and Book Layout
  • 2: Theoretical Background
  • 2.1 Preliminaries of Distributed Systems
  • 2.1.1 Problem Description
  • 2.1.2 Control Design Scheme
  • 2.1.3 Without Communication Delays
  • 2.1.4 With Communication Delays
  • 2.2 Networked Multiagent Systems
  • 2.2.1 Consensus in Networks
  • 2.2.2 The f-Consensus Problem
  • 2.2.3 Iterative Consensus and Markov Chains
  • 2.3 Applications
  • 2.3.1 Synchronization of Coupled Oscillators
  • 2.3.2 Flocking Theory
  • 2.3.3 Fast Consensus in Small-Worlds
  • 2.3.4 Rendezvous in Space
  • 2.3.5 Distributed Sensor Fusion in Sensor Networks
  • 2.3.6 Distributed Formation Control
  • 2.4 Information Consensus
  • 2.4.1 Algebraic Connectivity and Spectral Properties
  • 2.4.2 Convergence Analysis for Directed Networks
  • 2.4.3 Consensus in Discrete-Time
  • 2.4.4 Performance of Consensus Algorithms
  • 2.4.5 Alternative Forms of Consensus Algorithms
  • 2.4.6 Weighted-Average Consensus
  • 2.4.7 Consensus Under Communication Time-Delays
  • 2.5 Consensus in Switching Networks
  • 2.6 Cooperation in Networked Control Systems
  • 2.6.1 Collective Dynamics of Multivehicle Formation
  • 2.6.2 Stability of Relative Dynamics
  • 2.7 Simulation Studies
  • 2.7.1 Consensus in Complex Networks
  • 2.7.2 Multivehicle Formation Control
  • 2.8 Notes
  • 3: Distributed Intelligence in Power Systems
  • 3.1 Introduction to MAS Technology
  • 3.1.1 Autonomous Microgrid System
  • 3.1.2 A State-Space Model
  • 3.1.3 Heuristic Dynamic Programming
  • 3.1.4 Discrete-Time Bellman Equation
  • 3.1.5 Value Iteration Algorithm
  • 3.1.6 Adaptive Critics Implementation
  • 3.1.7 Actor-Critic Implementation
  • 3.1.8 Simulations Results
  • 3.1.9 Actor-Critic Tuning Results
  • 3.1.10 Robustness of the Proposed Controller
  • 3.2 Operation in Islanded Mode
  • 3.2.1 Autonomous Microgrid
  • 3.2.2 Primary Control
  • 3.2.3 Fixed Gain Distributed Secondary Control
  • 3.2.4 Neural Network Distributed Secondary Control
  • 3.2.5 Stage 1: Selection of Training Data
  • 3.2.6 Stage 2: Selection of Artificial Neural Network

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