Robust Cooperative Control of Multi-Agent Systems: A Prediction and Observation ProspectiveКНИГИ » ТЕХНИЧЕСКИЕ НАУКИ
Название: Robust Cooperative Control of Multi-Agent Systems: A Prediction and Observation Prospective Автор: Chunyan Wang, Zongyu Zuo Издательство: CRC Press Год: 2021 Страниц: 231 Язык: английский Формат: pdf (true) Размер: 24.8 MB
This book presents a concise introduction to the latest advances in robust cooperative control design for multi-agent systems with input delay and external disturbances, especially from a prediction and observation perspective. The volume covers a wide range of applications, such as the trajectory tracking of quadrotors, formation flying of multiple unmanned aerial vehicles (UAVs) and fixed-time formation of ground vehicles.
In the control community, “multi-agent systems” is a term used to describe a group of agents which are connected together to achieve specified control tasks over a communication network. Cooperative control of multi-agent systems has emerged as an attractive area of research in the last two decades and has been widely used in the real world, including wheeled robotic systems, satellites, autonomous underwater vehicles (AUVs), spacecraft, unmanned aerial vehicles (UAVs), sensor network, surveillance, smart grids, etc. In the formulation of cooperative control, there are two types of methods in the literature: centralized method and distributed method. Compared to centralized method which uses a core cell to control and connect a group of agents, the distributed method, which uses the local information to design distributed controllers, brings a number of benefits. For example, distributed multi-agent systems are more tolerant to bad environments, since failure of one agent does not seriously effect the performance of the whole system. Consensus control is a fundamental problem in distributed cooperative control, since many applications are based on the consensus algorithm design.
Robust cooperative control means that multi-agent systems are able to achieve specified control tasks while remaining robust in the face of both parametric and nonparametric model uncertainties. In addition, the authors cover a wide range of key issues in cooperative control, such as communication and input delays, parametric model uncertainties and external disturbances. Moving beyond the scope of existing works, a systematic prediction and observation approach to designing robust cooperative control laws is presented.
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