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Multiagent Scheduling : Models and Algorithms
Scheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion. In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures.
Book
Graph theoretic methods in multiagent networks
This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems.
The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications.
The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications.
This book has been adopted as a textbook at the following universities:
University of Stuttgart, GermanyRoyal Institute of Technology, SwedenJohannes Kepler University, AustriaGeorgia Tech, USAUniversity of Washington, USAOhio University, USA
eBook
Formation Control of Multi-Agent Systems
A comprehensive guide to formation control of multi-agent systems using rigid graph theory This book is the first to provide a comprehensive and unified treatment of the subject of graph rigidity-based formation control of multi-agent systems.
eBook
Practically fixed-time adaptive consensus control for multiagent systems with prescribed performance
In this paper, the fixed-time consensus tracking control problem of multiagent systems (MASs) subject to unknown nonlinearities and performance constraints is investigated. Initially, an improved fixed-time performance function is designed, which enables the consensus tracking errors to converge to the preset region in fixed time, and alleviates the initial error conditions by setting the parameters appropriately. Moreover, the unknown nonlinearities of MASs are approximated by the radial basis function neural network (RBF NN). Subsequently, a fixed-time prescribed performance controller is designed, which excludes the fractional power of tracking error to prevent potential singularity problems existing in stability proof. Additionally, a fixed-time dynamic surface filter is formulated to eliminate the “explosion of complexity” issue, meanwhile, the filter errors are bounded in fixed time. Utilizing the Lyapunov stability theory, it can be guaranteed that all signals in MASs exhibit practically fixed-time stability, and the consensus errors all approach a small region centered on origin within the prescribed bounds. Finally, simulations are presented to verify the validity of the proposed control strategy.
Journal Article
Observer-Based Consensus of Higher-Order Nonlinear Heterogeneous Multiagent Systems with Unmatched Uncertainties: Application on Robotic Systems
The consensus of higher-order nonlinear heterogeneous multiagent systems with matched and unmatched uncertainties is studied in this paper. The distributed observer-based controllers for multiagent systems are achieved using a fixed-time sliding mode controller based on the disturbance observer. For this purpose, the disturbance observers are designed for finite-time estimation of matched and unmatched uncertainties. Using the estimated values, the fixed-time distributed sliding mode controllers are designed and the consensus protocol is achieved. In this regard, a theorem is proved, which guarantees the fixed-time convergence of consensus errors. The effectiveness of the proposed distributed controllers has been validated through simulations for two robotic multiagent systems and a numerical example.
Journal Article
Impulsive fault-tolerant adaptive control on second-order nonlinear multiagent systems by extended observer approach
This paper investigates the consensus of multiagent systems based on impulsive control with actuator faults. A typical fault that the actuator has partial loss of effectiveness (PLOE) with multiple modes is taken into consideration. Two main adaptive control schemes are designed to solve the tracking consensus problem with second-order nonlinear agent model. On the one hand, to estimate the PLOE mode, an asynchronous impulsive adaptive scheme using full system information is presented and the consensus proves to be achieved under sufficient conditions. On the other hand, by considering each agent as an input–output system, an impulsive adaptive scheme with extended observers is introduced with only output information available. The consensus first proves to be achieved by a method using time-varying linear matrix inequalities (LMIs) theoretically. However, it is difficult to obtain certain solutions of the time-varying LMIs for condition checking. Then, the feasibility analysis is made and an alternative scheme is proposed to deal with this issue instead. Numerical simulations are presented to support the theoretical results.
Journal Article