Huaicheng Yan

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.

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.

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.