Robotic systems have experienced exponential growth thanks to their incredible adaptability. Modern robots require an increasing level of autonomy, safety and reliability. This book addresses the challenges of increasing and ensuring reliability and safety of modern robotic and autonomous systems. The book provides an overview of research in this field to-date, and addresses advanced topics including fault diagnosis and fault-tolerant control, and the challenging technologies and applications in industrial robotics, robotic manipulators, mobile robots, and autonomous and semi-autonomous vehicles.
Fault-tolerant control aims at a gradual shutdown response in automated systems when faults occur. It satisfies the industrial demand for enhanced availability and safety, in contrast to traditional reactions to faults, which bring about sudden shutdowns and loss of availability. The book presents effective model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, to test the fault detectability and to find the redundancies in the process that can be used to ensure fault tolerance. It also introduces design methods suitable for diagnostic systems and fault-tolerant controllers for continuous processes that are described by analytical models of discrete-event systems represented by automata. The book is suitable for engineering students, engineers in industry and researchers who wish to get an overview of the variety of approaches to process diagnosis and fault-tolerant control. The authors have extensive teaching experience with graduate and PhD students, as well as with industrial experts. Parts of this book have been used in courses for this audience. The authors give a comprehensive introduction to the main ideas of diagnosis and fault-tolerant control and present some of their most recent research achievements obtained together with their research groups in a close cooperation with European research projects. The third edition resulted from a major re-structuring and re-writing of the former edition, which has been used for a decade by numerous research groups. New material includes distributed diagnosis of continuous and discrete-event systems, methods for reconfigurability analysis, and extensions of the structural methods towards fault-tolerant control. The bibliographical notes at the end of all chapters have been up-dated. The chapters end with exercises to be used in lectures.
This book presents model-based analysis and design methods for fault diagnosis and fault-tolerant control. Architectural and structural models are used to analyse the propagation of the fault through the process, test fault detectability and reveal redundancies that can be used to ensure fault tolerance. Case studies demonstrate the methods presented. The second edition includes new material on reconfigurable control, diagnosis of nonlinear systems, and remote diagnosis, plus new examples and updated bibliography.
This book will play a central role in ensuring safe and reliable behaviour of intelligent and autonomous systems. It collects some of the most recent results in fault diagnosis and fault tolerant systems, with particular emphasis on mechatronic systems.
This book includes the thoroughly refereed post-conference proceedings of the 16th Annual RoboCup International Symposium, held in Mexico City, Mexico, in June 2012. The 24 revised papers presented together with nine champion team papers and one best paper award were carefully reviewed and selected from 64 submissions. The papers present current research and educational activities within the fields of Robotics and Artificial Intelligence with a special focus to robot hardware and software, perception and action, robotic cognition and learning, multi-robot systems, human-robot interaction, education and edutainment, and applications.
Distributed robotics is a rapidly growing, interdisciplinary research area lying at the intersection of computer science, communication and control systems, and electrical and mechanical engineering. The goal of the Symposium on Distributed Autonomous Robotic Systems (DARS) is to exchange and stimulate research ideas to realize advanced distributed robotic systems. This volume of proceedings includes 43 original contributions presented at the Tenth International Symposium on Distributed Autonomous Robotic Systems (DARS 2010), which was held in November 2010 at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. The selected papers in this volume are authored by leading researchers from Asia, Europa, and the Americas, thereby providing a broad coverage and perspective of the state-of-the-art technologies, algorithms, system architectures, and applications in distributed robotic systems. The book is organized into four parts, each representing one critical and long-term research thrust in the multi-robot community: distributed sensing (Part I); localization, navigation, and formations (Part II); coordination algorithms and formal methods (Part III); modularity, distributed manipulation, and platforms (Part IV).
Robust Control of Robots bridges the gap between robust control theory and applications, with a special focus on robotic manipulators. It is divided into three parts: robust control of regular, fully-actuated robotic manipulators; robust post-failure control of robotic manipulators; and robust control of cooperative robotic manipulators. In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system. They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB®-based simulation program freely available from the authors. The target audience for Robust Control of Robots includes researchers, practicing engineers, and graduate students interested in implementing robust and fault tolerant control methodologies to robotic manipulators.
This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics. Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome. We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.
Aerospace vehicles are by their very nature a crucial environment for safety-critical systems. By virtue of an effective safety control system, the aerospace vehicle can maintain high performance despite the risk of component malfunction and multiple disturbances, thereby enhancing aircraft safety and the probability of success for a mission. Autonomous Safety Control of Flight Vehicles presents a systematic methodology for improving the safety of aerospace vehicles in the face of the following occurrences: a loss of control effectiveness of actuators and control surface impairments; the disturbance of observer-based control against multiple disturbances; actuator faults and model uncertainties in hypersonic gliding vehicles; and faults arising from actuator faults and sensor faults. Several fundamental issues related to safety are explicitly analyzed according to aerospace engineering system characteristics; while focusing on these safety issues, the safety control design problems of aircraft are studied and elaborated on in detail using systematic design methods. The research results illustrate the superiority of the safety control approaches put forward. The expected reader group for this book includes undergraduate and graduate students but also industry practitioners and researchers. About the Authors: Xiang Yu is a Professor with the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests include safety control of aerospace engineering systems, guidance, navigation, and control of unmanned aerial vehicles. Lei Guo, appointed as "Chang Jiang Scholar Chair Professor", is a Professor with the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests include anti-disturbance control and filtering, stochastic control, and fault detection with their applications to aerospace systems. Youmin Zhang is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Québec, Canada. His research interests include fault diagnosis and fault-tolerant control, and cooperative guidance, navigation, and control (GNC) of unmanned aerial/space/ground/surface vehicles. Jin Jiang is a Professor in the Department of Electrical & Computer Engineering, Western University, London, Ontario, Canada. His research interests include fault-tolerant control of safety-critical systems, advanced control of power plants containing non-traditional energy resources, and instrumentation and control for nuclear power plants.
The seriesAdvancesinIndustrialControl aims to report and encourage te- nologytransfer in controlengineering. The rapid development of controlte- nology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies. . . , new challenges. Much of this devel- ment work resides in industrial reports, feasibility study papers, and the - ports of advanced collaborative projects. The series o?ers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Control system design and technology continues to develop in many d- ferent directions. One theme that the Advances in Industrial Control series is following is the application of nonlinear control design methods, and the series has some interesting new commissions in progress. However, another theme of interest is how to endow the industrial controller with the ability to overcome faults and process degradation. Fault detection and isolation is a broad ?eld with a research literature spanning several decades. This topic deals with three questions: • How is the presence of a fault detected? • What is the cause of the fault? • Where is it located? However, there has been less focus on the question of how to use the control system to accommodate and overcome the performance deterioration caused by the identi?ed sensor or actuator fault.
