Xiwang Dong – författare

Resilient Cooperative Control and Optimization of Multi-Agent Systems addresses various resilient cooperative control and optimization problems of multi-agent systems that are vulnerable to physical failure and cyber attacks and consist of multiple decision-making agents that interact in a shared environment to achieve common or conflicting goals. Critical infrastructures, such as smart grids, wireless sensor network, multi-robot system, etc., are typical examples of multi-agent systems that consist of the large-scale physical processes which are monitored and controlled over a set of communication networks and computers.Presents solutions to different resilient cooperative control and optimization problems of multi-agent systemsIncludes a wealth of examples on attack-resilient consensus control, time-varying formation tracking control, distributed optimization and distributed Nash equilibrium game-seekingShows, in detail, the practicalities of how to develop an attack-resilient cooperative control and optimization framework

Swarm system, also known as multi-agent system, refers to a system composed of multiple subsystems (agents) with certain communication, calculation, decision-making, and action capabilities through local information interaction, such as a group of unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), satellites, etc. Formation tracking control of swarm systems is an important technical support and approach for the emergence of swarm intelligence at motion control level. By applying formation tracking control, swarm system agents can adjust their relations in the state or output space through neighboring information interaction, and then the swarm system can achieve favorable space-time conditions for many cooperative tasks such as source seeking, target enclosing, and surveillance. Thus, complex missions can be performed efficiently or cost-effectively. In cross-domain collaborative applications, including air-ground coordination and air-sea coordination, swarm systems are usually composed of several heterogeneous agents, and swarm intelligence can be enhanced by complementary functions of different agents. How to achieve time-varying formation tracking for heterogeneous swarm systems is crucial for cross-domain coordination, which has important theoretical value and practical significance. This important book presents a systematic theoretical approach and control framework on the time-varying formation tracking for high-order heterogeneous swarm systems. Distributed controller design and stability analysis of closed-loop systems for several specific formation tracking problems are provided. Furthermore, the proposed control approaches are applied to practical cooperative experiment platforms composed of UAVs and UGVs, and several formation tracking experiments are carried out to further verify the effectiveness of the theories.

Swarm system, also known as multi-agent system, refers to a system composed of multiple subsystems (agents) with certain communication, calculation, decision-making, and action capabilities through local information interaction, such as a group of unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), satellites, etc. Formation tracking control of swarm systems is an important technical support and approach for the emergence of swarm intelligence at motion control level. By applying formation tracking control, swarm system agents can adjust their relations in the state or output space through neighboring information interaction, and then the swarm system can achieve favorable space-time conditions for many cooperative tasks such as source seeking, target enclosing, and surveillance. Thus, complex missions can be performed efficiently or cost-effectively. In cross-domain collaborative applications, including air-ground coordination and air-sea coordination, swarm systems are usually composed of several heterogeneous agents, and swarm intelligence can be enhanced by complementary functions of different agents. How to achieve time-varying formation tracking for heterogeneous swarm systems is crucial for cross-domain coordination, which has important theoretical value and practical significance. This important book presents a systematic theoretical approach and control framework on the time-varying formation tracking for high-order heterogeneous swarm systems. Distributed controller design and stability analysis of closed-loop systems for several specific formation tracking problems are provided. Furthermore, the proposed control approaches are applied to practical cooperative experiment platforms composed of UAVs and UGVs, and several formation tracking experiments are carried out to further verify the effectiveness of the theories.

This book focuses on analysis and design problems for high-order linear time-invariant (LTI) swarm systems (multi-agent systems) to achieve consensus, formation, containment and formation-containment. As a first step, the concepts of practical consensus and formation-containment are introduced. Unlike previous research, the formation in this book can be time-varying. A general framework for consensus, consensus tracking, formation, containment and state formation-containment is presented for the first time.Sufficient/necessary and sufficient conditions, and approaches to designing the protocols for swarm systems to achieve these control objectives, are respectively proposed. Autonomous time-varying formation experiments using five quadrotor unmanned aerial vehicles (UAVs) are conducted in an outdoor setting to demonstrate the theoretical results.

This book focuses on analysis and design problems for high-order linear time-invariant (LTI) swarm systems (multi-agent systems) to achieve consensus, formation, containment and formation-containment. As a first step, the concepts of practical consensus and formation-containment are introduced. Unlike previous research, the formation in this book can be time-varying. A general framework for consensus, consensus tracking, formation, containment and state formation-containment is presented for the first time.Sufficient/necessary and sufficient conditions, and approaches to designing the protocols for swarm systems to achieve these control objectives, are respectively proposed. Autonomous time-varying formation experiments using five quadrotor unmanned aerial vehicles (UAVs) are conducted in an outdoor setting to demonstrate the theoretical results.

This book includes original, peer-reviewed research papers from the 2025 9th Chinese Conference on Swarm Intelligence and Cooperative Control (CCSICC2025), held in Shanghai, China from Oct. 31 to Nov. 3, 2025. The contributions cover a broad spectrum of research topics, including but not limited to: reviews and discussions of swarm intelligence, basic theories on swarm intelligence, swarm communication and networking, swarm perception, awareness and location, swarm decision and planning, cooperative control, cooperative guidance, swarm simulation, and assessment.The presented works report recent advances in theoretical analysis, algorithm design, and application-oriented research, highlighting both mature techniques and emerging research directions. This book is intended for researchers and practitioners engaged in swarm intelligence and cooperative control, as well as postgraduate students pursuing advanced studies in related fields.

The topics covered include but are not limited to: reviews and discussions of swarm intelligence, basic theories on swarm intelligence, swarm communication and networking, swarm perception, awareness and location, swarm decision and planning, cooperative control, cooperative guidance, swarm simulation and assessment.

This book includes original, peer-reviewed research papers from the 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control (CCSICC2023), held in Nanjing, China on November 17-19, 2023. The topics covered include but are not limited to: reviews and discussions of swarm intelligence, basic theories on swarm intelligence, swarm communication and networking, swarm perception, awareness and location, swarm decision and planning, cooperative control, cooperative guidance, swarm simulation and assessment. The papers showcased here share the latest findings on theories, algorithms and applications in swarm intelligence and cooperative control, making the book a valuable asset for researchers, engineers, and university students alike.

The book focuses on time-varying formation control approaches for practical nonlinear swarm systems.