Distributed Fault Tolerant Consensus Control Of Leader Following Systems

This book presents few novel Discrete-time Sliding Mode (DSM) protocols for leader-following consensus of Discrete Multi-Agent Systems (DMASs). The protocols intend to achieve the consensus in finite time steps and also tackle the corresponding uncertainties. Based on the communication graph topology of multi-agent systems, the protocols are divided into two groups, namely (i) Fixed graph topology and (ii) Switching graph topology. The coverage begins with the design of Discrete-time Sliding Mode (DSM) protocols using Gao’s reaching law and power rate reaching law for the synchronization of linear DMASs by using the exchange of information between the agents and the leader to achieve a common goal. Then, in a subsequent chapter, analysis for no. of fixed-time steps required for the leader-following consensus is presented. The book also includes chapters on the design of Discrete-time Higher-order Sliding Mode (DHSM) protocols, Event-triggered DSM protocols for the leader-following consensus of DMASs. A chapter is also included on the design of DHSM protocols for leader-following consensus of heterogeneous DMASs. Special emphasis is given to the practical implementation of each proposed DSM protocol for achieving leader-following consensus of helicopter systems, flexible joint robotic arms, and rigid joint robotic arms. This book offers a ready reference guide for graduate students and researchers working in the areas of control, automation, and communication engineering, and in particular the cooperative control of multi-agent systems. It will also benefit professional engineers working to design and implement robust controllers for power systems, autonomous vehicles, military surveillance, smartgrids/microgrids, vehicle traffic management, robotic teams, and aerial robots.

This book is concerned with the fault estimation problem for network systems. Firstly, to improve the existing adaptive fault estimation observer, a novel so-called intermediate estimator is proposed to identify the actuator or sensor faults in dynamic control systems with high accuracy and convergence speed. On this basis, by exploiting the properties of network systems such as multi-agent systems and large-scale interconnected systems, this book introduces the concept of distributed intermediate estimator; faults in different nodes can be estimated simultaneously; meanwhile, satisfactory consensus performances can be obtained via compensation based protocols. Finally, the characteristics of the new fault estimation methodology are verified and discussed by a series of experimental results on networked multi-axis motion control systems. This book can be used as a reference book for researcher and designer in the field of fault diagnosis and fault-tolerant control and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.

The book presents latest multi-agent technologies in human-centered computing (HCC) to provide a new research direction to enrich the human socio computations. Nowadays, the research in the field of multi-agent system (MAS) has gained a wide spread recognition due to its interdisciplinary nature and a vast versatile application domain including engineering, social science, economics, mathematics, operational research, etc. It has been proved that agents in MAS are the most appropriate technological paradigm for providing the most optimal solution for different kinds of complex real world problems that may be industrial or it might be specifically related to social problems. Keeping these features in mind, we planned to tune the research of latest multi-agent technologies and tried to compose its effect on HCC corridor. The primary audience of this book are research students of computer science, information technology and it will be also very helpful for software professionals to get developmental ideas to boost their computing activities.

This book presents selected research papers from CISC’17, held in MudanJiang, China. The topics covered include Multi-agent system, Evolutionary Computation, Artificial Intelligence, Complex systems, Computation intelligence and soft computing, Intelligent control, Advanced control technology, Robotics and applications, Intelligent information processing, Iterative learning control, Machine Learning, and etc. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.

This book explores admissible consensus analysis and design problems concerning singular multi-agent systems, addressing various impact factors including time delays, external disturbances, switching topologies, protocol states, topology structures, and performance constraint. It also discusses the state-space decomposition method, a key technique that can decompose the motions of singular multi-agent systems into two parts: the relative motion and the whole motion. The relative motion is independent of the whole motion. Further, it describes the admissible consensus analysis and determination of the design criteria for different impact factors using the Lyapunov method, the linear matrix inequality tool, and the generalized Riccati equation method. This book is a valuable reference resource for graduate students of control theory and engineering and researchers in the field of multi-agent systems.