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This book aims to extend existing works on consensus of multi-agent systems systematically. The agents to be considered range from double integrators to generic linear systems. The primary goal is to explicitly characterize how agent parameters, which reflect both self-dynamics and inner coupling of each agent, and switching network topologies jointly influence the collective behaviors. A series of necessary and/or sufficient conditions for exponential consensus are derived. The contents of this book are as follows. Chapter 1 provides the background and briefly reviews the advances of consensus of multi-agent systems. Chapter 2 addresses the consensus problem of double integrators over directed switching network topologies. It is proven that exponential consensus can be secured under very mild conditions incorporating the damping gain and network topology. Chapter 3 considers generic linear systems with undirected switching network topologies. Necessary and sufficient conditions on agent parameters and connectivity of the communication graph for exponential consensus are provided. Chapter 4 furthers the study of consensus for multiple generic linear systems by considering directed switching network topologies. How agent parameters and joint connectivity work together for reaching consensus is characterized from an algebraic and geometric view. Chapter 5 extends the design and analysis methodology to containment control problem, where there exist multiple leaders. A novel analysis framework from the perspective of state transition matrix is developed. This framework relates containment to consensus and overcomes the difficulty of construction of a containment error.This book serves as a reference to the main research issues and results on consensus of multi-agent systems. Some prerequisites for reading this book include linear system theory, matrix theory, mathematics, and so on.

This book presents recent research work on stochastic jump hybrid systems. Specifically, the considered stochastic jump hybrid systems include Markovian jump Ito stochastic systems, Markovian jump linear-parameter-varying (LPV) systems, Markovian jump singular systems, Markovian jump two-dimensional (2-D) systems, and Markovian jump repeated scalar nonlinear systems. Some sufficient conditions are first established respectively for the stability and performances of those kinds of stochastic jump hybrid systems in terms of solution of linear matrix inequalities (LMIs). Based on the derived analysis conditions, the filtering and control problems are addressed.The book presents up-to-date research developments and novel methodologies on stochastic jump hybrid systems. The contents can be divided into two parts: the first part is focused on robust filter design problem, while the second part is put the emphasis on robust control problem. These methodologies provide a framework for stability and performance analysis, robust controller design, and robust filter design for the considered systems. Solutions to the design problems are presented in terms of LMIs.The book is a timely reflection of the developing area of filtering and control theories for Markovian jump hybrid systems with various kinds of imperfect information. It is a collection of a series of latest research results and therefore serves as a useful textbook for senior and/or graduate students who are interested in knowing 1) the state-of-the-art of linear filtering and control areas, and 2) recent advances in stochastic jump hybrid systems. The readers will also benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.