Cooperative Control of Multi-Agent Systems with Uncertainties (eBook)

Multi-agent coordination is an emerging engineering It has been inspired by the observations and descriptions of collective behavior in nature, such as fish schooling, birds flocking and insects swarming. The advantages of multi-agent coordination include: it can reduce cost and complexity from hardware platform to software and algorithms; in addition, multi-agent systems are capable of many tasks which could not be effectively performed by a single-robot system, for example, the surveillance task.  The book proposes a hierarchical design framework that places uncertainties related to system models in the decentralized control layer (bottom layer) and the ones related to the communication (as well as physical interaction) between the agents in the distributed decision-making layer (top layer). The book shows that the two layers meet the separation principle under certain conditions, so that through the two-layer design framework, any challenges can be resolved independently, and the design complexity will not increase with the level of uncertainties. In addition, in order to solve the problem of energy limitation of agents, this book also studies the event-driven cooperative control of multi-agent systems, which can effectively reduce the energy consumption of agents and increase their operational life span.  - Bridges the gap for engineers and technicians in the automation industry, including theory and practice - Provides a general framework for dealing with various uncertainties in multi-agent cooperative control problems - Contains contributions surrounding the development of multi-agent systems control theory

Prof. Hao Zhang received her doctorate degree from Huazhong University of Science and Technology, Wuhan, China, in 2007. She held lecturer's position at Tongji University, Shanghai, China, in 2007. In 2015, she was promoted to professor and doctoral supervisor. From 2011 to 2013, she also worked as a postdoctoral researcher at the City University of Hong Kong. She also conducted research visits at Griffith University in Australia, the University of Melbourne, and the University of Guelph in Canada. In 2018, she was selected into the Changjiang Young Scholars Program of the Ministry of Education of China. In 2019, she presided over the national fund for Outstanding Young Scholars Program. Her main research fields include: control of networked multi-agent systems, network security, multi-sensor information fusion, etc. More than 100 of her papers have been published in influential international journals and conferences, and more than 70 papers are included by SCI. Among them, more than 30 papers have been published in IEEE Transactions such as IEEE Transactions on Automatic Control and Automatica, and 13 papers have been selected as the top 1% highly cited papers in ESI. One paper was selected as 'China's 100 most influential international academic papers'. She is the editorial board member of IEEE Intelligent Transportation Systems Magazine, SCIENCE CHINA Information Sciences-Security and Safety, Intelligence & Robotics, and other international journals. She served as chairman / program member of WCICA, CCC, IEEE ICIA and other international conference associations. Her published papers have been cited by SCI for more than 1500 times, including more than 20 IEEE fellows and famous scholars in the field of systems and control, including fellows of the American Academy of Sciences and the Academy of engineering.

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Multi-agent coordination is an emerging engineering It has been inspired by the observations and descriptions of collective behavior in nature, such as fish schooling, birds flocking and insects swarming. The advantages of multi-agent coordination include: it can reduce cost and complexity from hardware platform to software and algorithms; in addition, multi-agent systems are capable of many tasks which could not be effectively performed by a single-robot system, for example, the surveillance task. The book proposes a hierarchical design framework that places uncertainties related to system models in the decentralized control layer (bottom layer) and the ones related to the communication (as well as physical interaction) between the agents in the distributed decision-making layer (top layer). The book shows that the two layers meet the separation principle under certain conditions, so that through the two-layer design framework, any challenges can be resolved independently, and the design complexity will not increase with the level of uncertainties. In addition, in order to solve the problem of energy limitation of agents, this book also studies the event-driven cooperative control of multi-agent systems, which can effectively reduce the energy consumption of agents and increase their operational life span. - Bridges the gap for engineers and technicians in the automation industry, including theory and practice- Provides a general framework for dealing with various uncertainties in multi-agent cooperative control problems- Contains contributions surrounding the development of multi-agent systems control theory