Huaicheng Yan – författare

Cooperative Control of Multi-Agent Systems with Uncertainties 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 separation principles under certain conditions so that through the two-layer design framework any challenges can be resolved independently and so that design complexities will not increase with the level of uncertainties.In addition, in order to solve the problem of energy limitation of agents, the book also studies the event-driven cooperative control of multi-agent systems, which can effectively reduce energy consumption of agents and increase their operational lifespan.

Bridges the gap for engineers and technicians in the automation industry, including theory and practiceProvides a general framework for dealing with various uncertainties in multi-agent cooperative control problemsContains contributions surrounding the development of multi-agent systems control theory

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

The book focuses on the analysis and synthesis of one-dimensional (1-D) and two-dimensional (2-D) fuzzy-model-based control systems. By exploiting available information of fuzzy systems, for example, membership functions, premise variable partition information, frequency spectrum of disturbances/faults and current/past output measurements, a basic theoretical framework is formed towards the issues of less conservative fuzzy-model-based analysis and synthesis for 1-D/2-D nonlinear systems. This is obtained by providing an in-depth study on several major topics such as membership function/piecewise Lyapunov function based stability analysis, sampled-data control, event-triggered state estimation, finite frequency control/filtering/fault detection, memory control/filtering for fuzzy systems. The comprehensive and systematic treatment of nonlinear systems based on fuzzy models is one of the major features of the book, which is particularly suitable for readers who are interested in learning fuzzy models and/or 1-D/2-D nonlinear systems. From this book, the reader can obtain the most advanced analysis and synthesis techniques for fuzzy-model-based nonlinear systems.

This book mainly focuses on the key technologies and important issues related to cyberattack strategy design against cyber-physical systems from the perspective of the attacker. Chapter 1 introduces the concept of cyber-physical systems, the significance of their cybersecurity, and research progress both domestically and internationally. Chapters 2–8 present research results on DoS attacks and FDI attacks under model-based, data-driven, time-varying delay, and game-based scenarios. This book demonstrates the effectiveness and superiority of the theoretical methods through simulation and physical examples. This provides defenders with insights into attack behaviors while establishing a theoretical foundation for developing more robust defense mechanisms.

This book mainly focuses on the key technologies and important issues related to cyberattack strategy design against cyber-physical systems from the perspective of the attacker. Chapter 1 introduces the concept of cyber-physical systems, the significance of their cybersecurity, and research progress both domestically and internationally. Chapters 2–8 present research results on DoS attacks and FDI attacks under model-based, data-driven, time-varying delay, and game-based scenarios. This book demonstrates the effectiveness and superiority of the theoretical methods through simulation and physical examples. This provides defenders with insights into attack behaviors while establishing a theoretical foundation for developing more robust defense mechanisms.

This book mainly focuses on the key technologies and important issues related to localization estimation and formation control for networked multi-agent systems. Chapter 1 introduces the concepts of multi-agent systems, fundamental issues in localization and formation, research progress both at home and abroad, and the theory of system stability. Chapters 2–8 present research results on distributed localization estimation under conditions such as random deployment, non-ideal channels, random noise, varying-trajectory length, sensor multiplicative failure, and local bearing measurement. Chapter 9 focuses on integrated research progress in localization estimation and formation control for multi-agent systems under local perception conditions. The book demonstrates the effectiveness and superiority of the theoretical methods through simulation and physical examples.