Multi Agent Control

This book gathers the peer-reviewed papers presented at the 8th edition of the International Workshop “Service Orientation in Holonic and Multi-Agent Manufacturing – SOHOMA’18” held at the University of Bergamo, Italy on June 11–12, 2018. The objective of the SOHOMA annual workshops is to foster innovation in smart and sustainable manufacturing and logistics systems by promoting new concepts, methods and solutions that use service orientation of agent-based control technologies with distributed intelligence.

The scientific theme of the book concerns “Manufacturing as a Service (MaaS)” which is developed in a layered cloud networked manufacturing perspective, from the shop floor resource sharing model to the virtual enterprise collaborative model, by distributing the cost of the manufacturing infrastructure - equipment, software, maintenance, networking - across all customers.

This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. This book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems.

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.