Consensus of Multi-Agent Systems with Binary-Valued Measurements

1 Introduction
1.1 Motivation
1.2 Identification of Set-Valued Systems
1.3 Consensus Control of Multi-Agent Systems
1.4 Outline of the Book
2 Preliminaries
2.1 Vectors and Norms
2.2 Probability Theory
2.3 Algebraic Graph Theory
2.4 Some Other Concepts
2.5 Notes
3 Identification of Set-Valued Systems
3.1 Problem Formulation
3.2 Asymptotically Efficient Non-Truncated Identification Algorithm
3.2.1 Identification for Single-Parameter Systems
3.2.2 Identification for Multi-Parameter Systems
3.2.3 Numerical Simulation
3.3 Recursive Projection Identification Algorithm
3.3.1 Algorithm Design
3.3.2 Properties of the Algorithm
3.3.3 Numerical Simulation
3.4 Notes
4 Consensus with Binary-Valued Measurements under Undirected Topology
4.1 Problem Formulation
4.2 Two-Time-Scale Consensus
4.2.1 Estimation
4.2.2 Consensus Control
4.2.3 The Consensus Protocol
4.2.4 Numerical Simulation
4.3 Recursive Projection Consensus
4.3.1 Consensus Algorithm
4.3.2 Main Results
4.3.3 Numerical Simulation
4.4 Notes
5 Consensus with Binary-Valued Measurements under Directed Topology
5.1 Problem Formulation
5.2 Control Algorithm
5.3 Properties of the Algorithm
5.3.1 Estimation
5.3.2 Transportation Design
5.4 Numerical Simulation
5.5 Notes
6 Consensus of Linear Multi-Agent Systems with Binary-Valued Measurements
6.1 Problem Formulation
6.2 Review on the Case of Precise Communication
6.3 Case of Binary-Valued Communication
6.3.1 Control Algorithm
6.3.2 Main Results
6.4 Numerical Simulation
6.5 Notes
References