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This book investigates the distributed impulsive coordination control of multi-agent systems (MASs), including consensus problem and formation problem. Compared with continuous control, impulsive control as a discontinuous control method only needs information interaction at impulsive instants, which can greatly reduce the transmission cost in the communication process. In practice, MASs are often affected by environmental and hardware conditions, resulting in the application of impulsive control is limited. For example, it is difficult to exert the impulsive control signal accurately at a fixed instant, and it is difficult to control all agents at the same impulsive instant. Moreover, the actual models of MASs often contain some constraints such as unknown parameters, stochastic perturbation, and time delays. In addition, stochastic switching topologies and cyberattacks will limit the communication between agents in MASs, which will greatly affect the coordination control performance. Based on the existing research results, this book considers the above constraints of MASs in practice and studies the key problems of distributed impulsive coordination control for MASs. The book is intended for undergraduate and graduate students who are interested in control system theory, as well as engineers studying MASs.
Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.
Based on a suitably defined coordination model distinguishing between objective (inter-agent) coordination and subjective (intra-agent) coordination, this book addresses the engineering of multi-agent systems and thus contributes to closing the gap between research and applications in agent technology. After reviewing the state of the art, the author introduces the general coordination model ECM and the corresponding object-oriented coordination language STL++. The practicability of ECM/STL++ is illustrated by the simulation of a particular collective robotics application and the automation of an e-commerce trading system. Situated at the intersection of behavior-based artificial intelligence and concurrent and distributed systems, this monograph is of relevance to the agent R&D community approaching agent technology from the distributed artificial intelligence point of view as well as for the distributed systems community.
Challenges arise when the size of a group of cooperating agents is scaled to hundreds or thousands of members. In domains such as space exploration, military and disaster response, groups of this size (or larger) are required to achieve extremely complex, distributed goals. To effectively and efficiently achieve their goals, members of a group need to cohesively follow a joint course of action while remaining flexible to unforeseen developments in the environment. Coordination of Large-Scale Multiagent Systems provides extensive coverage of the latest research and novel solutions being developed in the field. It describes specific systems, such as SERSE and WIZER, as well as general approaches based on game theory, optimization and other more theoretical frameworks. It will be of interest to researchers in academia and industry, as well as advanced-level students.
The thesis presents new results on multi-agent formation control, focusing on the distributed stabilization control of rigid formation shapes. It analyzes a range of current research problems such as problems concerning the equilibrium and stability of formation control systems, or the problem of cooperative coordination control when agents have general dynamical models, and discusses practical considerations arising during the implementation of established formation control algorithms. In addition, the thesis presents models of increasing complexity, from single integrator models, to double integrator models, to agents modeled by nonlinear kinematic and dynamic equations, including the familiar unicycle model and nonlinear system equations with drift terms. Presenting the fruits of a close collaboration between several top control groups at leading universities including Yale University, Groningen University, Purdue University and Gwangju Institute of Science and Technology (GIST), the thesis spans various research areas, including robustness issues in formations, quantization-based coordination, exponential stability in formation systems, and cooperative coordination of networked heterogeneous systems.
An Application Science For Multi-Agent Systems addresses the complexity of choosing which multi-agent control technologies are appropriate for a given problem domain or a given application. Without such knowledge, when faced with a new application domain, agent developers must rely on past experience and intuition to determine whether a multi-agent system is the right approach, and if so, how to structure the agents, how to decompose the problem, and how to coordinate the activities of the agents, and so forth. This unique collection of contributions, written by leading international researchers in the agent community, provides valuable insight into the issues of deciding which technique to apply and when it is appropriate to use them. The contributions also discuss potential trade-offs or caveats involved with each decision. An Application Science For Multi-Agent Systems is an excellent reference for anyone involved in developing multi-agent systems.
Based on a suitably defined coordination model distinguishing between objective (inter-agent) coordination and subjective (intra-agent) coordination, this book addresses the engineering of multi-agent systems and thus contributes to closing the gap between research and applications in agent technology. After reviewing the state of the art, the author introduces the general coordination model ECM and the corresponding object-oriented coordination language STL++. The practicability of ECM/STL++ is illustrated by the simulation of a particular collective robotics application and the automation of an e-commerce trading system. Situated at the intersection of behavior-based artificial intelligence and concurrent and distributed systems, this monograph is of relevance to the agent R&D community approaching agent technology from the distributed artificial intelligence point of view as well as for the distributed systems community.