The paradigm of βmulti-agentβ cooperative control is the challenge frontier for new control system application domains, and as a research area it has experienced a considerable increase in activity in recent years. This volume, the result of a UCLA collaborative project with Caltech, Cornell and MIT
Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems
β Scribed by Wei Wang, Jiang Long, Jiangshuai Huang, Changyun Wen
- Publisher
- CRC Press
- Year
- 2025
- Tongue
- English
- Leaves
- 219
- Series
- Automation and Control Engineering
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
Preface
Authors
Chapter 1: Introduction
1.1. Adaptive Control
1.2. Consensus Control
1.3. Motivation
1.3.1. Adaptive Consensus Control
1.3.2. Adaptive Finite-Time Consensus Control
1.3.3. Event-Triggered Adaptive Consensus Control
1.4. Objectives
1.5. Preview of Chapters
Chapter 2: Preliminaries
2.1. Notations
2.2. Algebraic Graph Theory
2.3. Adaptive Backstepping Control
2.3.1. State Feedback Control
2.3.2. Output Feedback Control
2.4. Distributed Adaptive Consensus Control
2.4.1. Leader-Following Consensus Control
2.4.2. Leaderless Consensus Control
2.4.3. Discussion
2.5. Notes
SECTION I: Consensus Control under Directed Graph
Chapter 3: Distributed Adaptive State Feedback Control with Linearly Parametric Reference
3.1. Problem Formulation
3.2. An Illustrative Example
3.3. Design of Distributed Adaptive Controllers
3.4. Stability and Consensus Analysis
3.5. Simulation Results
3.6. Notes
Chapter 4: Auxiliary Filters-Based Distributed Adaptive Consensus Control
4.1. Problem Formulation
4.2. Design of Distributed Filters
4.3. Design of Local Adaptive Controllers
4.4. Stability and Consensus Analysis
4.5. Simulation Results
4.6. Notes
Chapter 5: Hierarchical Decomposition-Based Distributed Adaptive Consensus Control
5.1. Problem Formulation
5.2. Hierarchical Design of Distributed Adaptive Controllers
5.2.1. Hierarchical Decomposition
5.2.2. Design of Distributed Adaptive Controllers
5.3. Stability and Consensus Analysis
5.4. Simulation Results
5.5. Notes
SECTION II: Finite-Time Consensus Control
Chapter 6: Adaptive Finite-Time Consensus for Uncertain Nonlinear Mechanical Systems
6.1. Preliminaries
6.2. Problem Formulation
6.3. Adaptive Finite-Time Consensus Controller Design
6.4. Stability Analysis
6.5. Transient Performance Analysis
6.6. Simulation Results
6.7. Notes
SECTION III: Consensus Control with Event-Triggered Communication
Chapter 7: Distributed Event-Triggered Adaptive Control: Leader-Following Case
7.1. Problem Formulation
7.2. Preliminary Control Design with Continuous Communication
7.3. Control Design with Event-Triggered Communication
7.3.1. Design of Triggering Condition
7.3.2. Design of Distributed Adaptive Controllers
7.4. Stability and Consensus Analysis
7.5. Simulation Results
7.6. Notes
Chapter 8: Distributed Event-Triggered Adaptive Control: Leaderless Case
8.1. Problem Statement
8.2. Design of Distributed Adaptive Controllers
8.2.1. Design of Filters
8.2.2. Design of Triggering Conditions
8.2.3. Design of Distributed Adaptive Controllers
8.3. Stability and Consensus Analysis
8.4. A Consensus Performance-Related Switching Triggering Strategy
8.5. Simulation Results
8.6. Notes
Chapter 9: Distributed Event-Triggered Adaptive Output Feedback Control
9.1. Problem Formulation
9.2. Design of Distributed Adaptive Controllers with Event-Triggered Communication
9.2.1. Design of Local State Estimation Filters
9.2.2. Design of Time-Varying Triggering Rules
9.2.3. Design of Distributed Adaptive Controllers
9.3. Stability and Consensus Analysis
9.4. Simulation Results
9.5. Notes
SECTION IV: Applications
Chapter 10: Distributed Adaptive Formation Control of Nonholonomic Mobile Robots
10.1. Problem Formulation
10.1.1. System Model
10.1.2. Change of Coordinates
10.1.3. Formation Control Objective
10.2. Distributed Adaptive Formation Controller Design
10.3. Stability and Consensus Analysis
10.4. Simulation Results
10.5. Notes
Chapter 11: Distributed Event-Triggered Adaptive Attitude Synchronization of Multiple
11.1. Problem Formulation
11.1.1. Spacecraft Attitude Dynamics
11.1.2. Control Objective
11.2. The Case with Available Angular Velocity Measurements
11.2.1. Design of Distributed Reference Systems
11.2.2. Design of Distributed Adaptive Control Laws
11.2.3. Stability and Synchronization Analysis
11.3. The Case without Angular Velocity Measurements
11.3.1. Modification of Distributed Reference Systems
11.3.2. Design of Distributed Adaptive Output Feedback Control Laws
11.3.3. Stability and Synchronization Analysis
11.4. Experiment Results
11.4.1. Adaptive Attitude synchronization with Available Angular Velocity Measurements
11.4.2. Adaptive Attitude Synchronization without Angular Velocity Measurements
11.5. Notes
References
Index
π SIMILAR VOLUMES
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