Machine behavior design and analysis : a consensus perspective
著者
書誌事項
Machine behavior design and analysis : a consensus perspective
Springer, 2020
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注記
Includes bibliographical references
内容説明・目次
内容説明
In this book, we present our systematic investigations into consensus in multi-agent systems. We show the design and analysis of various types of consensus protocols from a multi-agent perspective with a focus on min-consensus and its variants. We also discuss second-order and high-order min-consensus. A very interesting topic regarding the link between consensus and path planning is also included. We show that a biased min-consensus protocol can lead to the path planning phenomenon, which means that the complexity of shortest path planning can emerge from a perturbed version of min-consensus protocol, which as a case study may encourage researchers in the field of distributed control to rethink the nature of complexity and the distance between control and intelligence. We also illustrate the design and analysis of consensus protocols for nonlinear multi-agent systems derived from an optimal control formulation, which do not require solving a Hamilton-Jacobi-Bellman (HJB) equation.
The book was written in a self-contained format. For each consensus protocol, the performance is verified through simulative examples and analyzed via mathematical derivations, using tools like graph theory and modern control theory. The book's goal is to provide not only theoretical contributions but also explore underlying intuitions from a methodological perspective.
目次
1 Introduction to Collective Machine Behavior
1.1 Collective Machine Behavior
1.2 Consensus
1.3 Theoretical Tools
1.4 Chapter Summary
References
2 Second-Order Min-Consensus
2.1 Introduction
2.2 Preliminary and Problem Formulation
2.3 Min-Consensus Under Switching Topology
2.4 Simulation Example
2.5 Chapter Summary
References
3 Consensus of High-Order Discrete-TimeMulti-Agent Systems
3.1 Introduction
3.2 Problem Description
3.3 Protocol Design
3.4 Theoretical Results
3.5 Illustrative Examples
3.6 Chapter Summary
References
4 Continuous-Time Biased Min-Consensus
4.1 Introduction
4.2 Background
4.3 Biased Min-Consensus
4.4 Equivalence to Shortest Path Planning
4.5 Simulations and Applications
4.6 Conclusions
References
5 Discrete-Time Biased Min-Consensus
5.1 Introduction
5.2 Preliminary
5.3 Discrete-Time Biased Min-Consensus
5.4 Algorithms
5.5 Numerical Investigations
5.6 Applications
5.7 Chapter Summary
References
6 Biased Consensus Based Distributed Neural Network
6.1 Introduction
6.2 Problem Formulation
6.3 Unified Scheme
6.4 Theoretical Results
6.5 Illustrative Examples
6.6 Extension to Path Planning of Mobile Robots
6.7 Chapter Summary
References
7 Predictive Suboptimal Consensus
7.1 Introduction
7.2 Preliminary
7.3 Control Law Design
7.4 Theoretical Results
7.5 Simulation Investigation
7.6 Chapter Summary
References
8 Adaptive Near-Optimal Consensus
8.1 Introduction
8.2 Problem Formulation
8.3 Nominal Near-Optimal Design
8.4 Adaptive Near-Optimal Design
8.5 Illustrative Example
8.6 Chapter Summary
References
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