This thesis proposes a method that plans trajectories for autonomous agents to enable them to fulfil different tasks while ensuring the collision-free movement. The agents are locally controlled and connected over an unreliable communication network that may induce packet losses and transmission delays. Further sensors e.g. for a distance measurement are not used and communication should only be invoked if it is necessary to avoid a collision. The basic problem occurs for two agents. The first agent can change its trajectory at any time without regard to the second agent, which has to ensure the collision avoidance. To this aim it adapts its trajectory based only on local data and communicated information about the current and future movement of the first agent. A control unit for the second agent is introduced that has to execute four tasks to ensure the control aims: 1. Estimation of the current network properties. 2. Prediction of the movement of the stand-on agent. 3. Invocation of communication whenever the local data becomes too uncertain. 4. Planning of collision avoiding trajectories. The main result of the thesis is a novel control method for mobile agents that solves the four tasks leading to a proven collision avoidance. The method consists of a delay estimator, a prediction unit, an event generator and a trajectory planning unit. The method can be used for different types of agents (e.g. UAVs or cars) with only slight modifications. The proposed method is tested and evaluated through simulations and experiments with both, two quadrotors and two nonholonomic robots.

A comprehensive review of the state of the art in the control of multi-agent systems theory and applications The superiority of multi-agent systems over single agents for the control of unmanned air, water and ground vehicles has been clearly demonstrated in a wide range of application areas. Their large-scale spatial distribution, robustness, high scalability and low cost enable multi-agent systems to achieve tasks that could not successfully be performed by even the most sophisticated single agent systems. Cooperative Control of Multi-Agent Systems: Theory and Applications provides a wide-ranging review of the latest developments in the cooperative control of multi-agent systems theory and applications. The applications described are mainly in the areas of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). Throughout, the authors link basic theory to multi-agent cooperative control practice — illustrated within the context of highly-realistic scenarios of high-level missions — without losing site of the mathematical background needed to provide performance guarantees under general working conditions. Many of the problems and solutions considered involve combinations of both types of vehicles. Topics explored include target assignment, target tracking, consensus, stochastic game theory-based framework, event-triggered control, topology design and identification, coordination under uncertainty and coverage control. Establishes a bridge between fundamental cooperative control theory and specific problems of interest in a wide range of applications areas Includes example applications from the fields of space exploration, radiation shielding, site clearance, tracking/classification, surveillance, search-and-rescue and more Features detailed presentations of specific algorithms and application frameworks with relevant commercial and military applications Provides a comprehensive look at the latest developments in this rapidly evolving field, while offering informed speculation on future directions for collective control systems The use of multi-agent system technologies in both everyday commercial use and national defense is certain to increase tremendously in the years ahead, making this book a valuable resource for researchers, engineers, and applied mathematicians working in systems and controls, as well as advanced undergraduates and graduate students interested in those areas.

This thesis concerns the cooperative control of networked vehicles. Autonomous driving is a topic that is currently being discussed with great interest from researchers, vehicle manufacturers and the corresponding media. Future autonomous vehicles should bring the passengers to their desired destination while improving both safety and efficiency compared to current human-driven vehicles. The inherent problem of all vehicle coordination tasks is to guarantee collision avoidance in every situation. To this end, autonomous vehicles have to share information with each other in order to perform traffic manoeuvres that require the cooperation of multiple vehicles. The fundamental problem of vehicle platooning is studied extensively which describes the task of arranging a set of vehicles so that they drive with a common velocity and a prescribed distance. Local design objectives are derived that have to be satisfied by the vehicle controllers. In particular, it is shown that the vehicles have to be externally positive to achieve collision avoidance. As an abstraction from real traffic scenarios, swarms of networked vehicles are considered. The main difference between swarming and traffic problems is that a communication structure that has been appropriate in the beginning might become unsuited for the control task due to the relative movement of the vehicles. To solve this problem, this thesis proposes to use the Delaunay triangulation as a switching communication structure.

Event-based systems are a class of reactive systems deployed in a wide spectrum of engineering disciplines including control, communication, signal processing, and electronic instrumentation. Activities in event-based systems are triggered in response to events usually representing a significant change of the state of controlled or monitored physical variables. Event-based systems adopt a model of calls for resources only if it is necessary, and therefore, they are characterized by efficient utilization of communication bandwidth, computation capability, and energy budget. Currently, the economical use of constrained technical resources is a critical issue in various application domains because many systems become increasingly networked, wireless, and spatially distributed. Event-Based Control and Signal Processing examines the event-based paradigm in control, communication, and signal processing, with a focus on implementation in networked sensor and control systems. Featuring 23 chapters contributed by more than 60 leading researchers from around the world, this book covers: Methods of analysis and design of event-based control and signal processing Event-driven control and optimization of hybrid systems Decentralized event-triggered control Periodic event-triggered control Model-based event-triggered control and event-triggered generalized predictive control Event-based intermittent control in man and machine Event-based PID controllers Event-based state estimation Self-triggered and team-triggered control Event-triggered and time-triggered real-time architectures for embedded systems Event-based continuous-time signal acquisition and DSP Statistical event-based signal processing in distributed detection and estimation Asynchronous spike event coding technique with address event representation Event-based processing of non-stationary signals Event-based digital (FIR and IIR) filters Event-based local bandwidth estimation and signal reconstruction Event-Based Control and Signal Processing is the first extensive study on both event-based control and event-based signal processing, presenting scientific contributions at the cutting edge of modern science and engineering.

Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value. It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.

This book showcases new theoretical findings and techniques in the field of intelligent systems and control. It presents in-depth studies on a number of major topics, including: Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control, Guidance, Navigation and Control of Aerial Vehicles, and so on. Given its scope, the book will benefit all researchers, engineers, and graduate students who want to learn about cutting-edge advances in intelligent systems, intelligent control, and artificial intelligence.

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