Iterative Learning Control for Multi-agent Systems Coordination
- Length: 272 pages
- Edition: 1
- Language: English
- Publisher: Wiley-IEEE Press
- Publication Date: 2017-05-30
- ISBN-10: 1119189047
- ISBN-13: 9781119189046
- Sales Rank: #3823461 (See Top 100 Books)
A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications
- Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS)
- Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes
- Covers basic theory, rigorous mathematics as well as engineering practice
Table of Contents
Chapter 1 Introduction
Chapter 2 Optimal Iterative Learning Control for Multi-agent Consensus Tracking
Chapter 3 Iterative Learning Control for Multi-agent Coordination Under Iteration-Varying Graph
Chapter 4 Iterative Learning Control for Multi-agent Coordination with Initial State Error
Chapter 5 Multi-agent Consensus Tracking with Input Sharing by Iterative Learning Control
Chapter 6 A HOIM-Based Iterative Learning Control Scheme for Multi-agent Formation
Chapter 7 P-type Iterative Learning for Non-parameterized Systems with Uncertain Local Lipschitz Terms
Chapter 8 Synchronization for Nonlinear Multi-agent Systems by Adaptive Iterative Learning Control
Chapter 9 Distributed Adaptive Iterative Learning Control for Nonlinear Multi-agent Systems with State Constraints
Chapter 10 Synchronization for Networked Lagrangian Systems under Directed Graphs
Chapter 11 Generalized Iterative Learning for Economic Dispatch Problem in a Smart Grid
Chapter 12 Summary and Future Research Directions
Appendix A Graph Theory Revisit
Appendix B Detailed Proofs
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