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Fault Detection and Isolation
“Fault Detection and Isolation: Multi-Vehicle Unmanned System” deals with the design and development of fault detection and isolation algorithms for unmanned vehicles such as spacecraft, aerial drones and other related vehicles. Addressing fault detection and isolation is a key step towards designing autonomous, fault-tolerant cooperative control of networks of unmanned systems. This book proposes a solution based on a geometric approach, and presents new theoretical findings for fault detection and isolation in Markovian jump systems. Also discussed are the effects of large environmental disturbances, as well as communication channels, on unmanned systems. The book proposes novel solutions to difficulties like robustness issues, as well as communication channel anomalies. “Fault Detection and Isolation: Multi-Vehicle Unmanned System” is an ideal book for researchers and engineers working in the fields of fault detection, as well as networks of unmanned vehicles.
Mathematical Models of Cancer and Different Therapies
This book provides a unified framework for various currently available mathematical models that are used to analyze progression and regression in cancer development, and to predict its dynamics with respect to therapeutic interventions. Accurate and reliable model representations of cancer dynamics are milestones in the field of cancer research. Mathematical modeling approaches are becoming increasingly common in cancer research, as these quantitative approaches can help to validate hypotheses concerning cancer dynamics and thus elucidate the complexly interlaced mechanisms involved. Even though the related conceptual and technical information is growing at an exponential rate, the applicati...
Social Robotics
The two-volume set LNAI 14453 and 14454 constitutes the refereed post-conference proceedings of the 15th International Conference on Social Robotics, ICSR 2023, held in Doha, Qatar, during December 4–7, 2023. The 68 revised full papers presented in these proceedings were carefully reviewed and selected from 83 submissions. They deal with topics around the interaction between humans and intelligent robots and on the integration of robots into the fabric of society. This year the special topic is "Human-Robot Collaboration: Sea; Air; Land; Space and Cyberspace”, focusing on all physical and cyber-physical domains where humans and robots collaborate.
Team Cooperation in a Network of Multi-Vehicle Unmanned Systems
Team Cooperation in a Network of Multi-Vehicle Unmanned Systems develops a framework for modeling and control of a network of multi-agent unmanned systems in a cooperative manner and with consideration of non-ideal and practical considerations. The main focus of this book is the development of “synthesis-based” algorithms rather than on conventional “analysis-based” approaches to the team cooperation, specifically the team consensus problems. The authors provide a set of modified “design-based” consensus algorithms whose optimality is verified through introduction of performance indices.
Heterogeneity in Breast Cancer: Clinical and Therapeutic Implications
Breast cancer is a highly heterogeneous disease. Despite advances in early detection and treatment, breast cancer (BC) is the leading cause of cancer death in women worldwide. Heterogeneity negatively affects a patient’s prognosis, treatment sensitivity, and clinical outcome. In particular, the development of drug resistance mechanisms and the failure of anticancer drugs (initially or subsequently) could lie in the heterogeneity among BC patients and tumors. The major international guidelines have adopted an immunophenotypic sub-classification of BC to maximize patient eligibility for personalized therapy but do not take into account the extreme diversity existing between breast tumors (intratumor heterogeneity).
Renewable Power for Sustainable Growth
This book is a collection of papers presented at the International Conference on Renewable Power (ICRP 2020), held during 13–14 July 2020 in Rajouri, Jammu, India. The book covers different topics of renewable energy sources in modern power systems. The book focusses on smart grid technologies and applications, renewable power systems including solar PV, solar thermal, wind, power generation, transmission and distribution, transportation electrification and automotive technologies, power electronics and applications in renewable power system, energy management and control system, energy storage in modern power system, active distribution network, artificial intelligence in renewable power systems, and cyber-physical systems and Internet of things in smart grid and renewable power.
Soft Computing in Condition Monitoring and Diagnostics of Electrical and Mechanical Systems
This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. The book’s goal is to develop and combine all advanced nonintrusive CMFD approaches on a common platform. To do so, it explores the main components of various systems used for CMFD purposes. The content is divided into three main parts, the first of which provides a brief introduction, before focusing on the state of the art and major research gaps in the area of CMFD. The second part covers the step-by-step implementation of novel soft computing applications in CMFD for electrical and mechanical systems. In the third and final part, the simulation codes for each chapter are included in an extensive appendix to support newcomers to the field.
Maneuverable Formation Control in Constrained Space
Inspired by the community behaviors of animals and humans, cooperative control has been intensively studied by numerous researchers in recent years. Cooperative control aims to build a network system collectively driven by a global objective function in a distributed or centralized communication network and shows great application potential in a wide domain. From the perspective of cybernetics in network system cooperation, one of the main tasks is to design the formation control scheme for multiple intelligent unmanned systems, facilitating the achievements of hazardous missions – e.g., deep space exploration, cooperative military operation, and collaborative transportation. Various chall...
Safe Autonomy with Control Barrier Functions
This book presents the concept of Control Barrier Function (CBF), which captures the evolution of safety requirements during the execution of a system and can be used to enforce safety. Safety is formalized using an emerging state-of-the-art approach based on CBFs, and many illustrative examples from autonomous driving, traffic control, and robot control are provided. Safety is central to autonomous systems since they are intended to operate with minimal or no human supervision, and a single failure could result in catastrophic results. The authors discuss how safety can be guaranteed via both theoretical and application perspectives. This presented method is computationally efficient and ca...
Explainable Artificial Intelligence for Intelligent Transportation Systems
Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can hardly be explained. This can be very problematic, especially for systems of a safety-critical nature such as transportation systems. Explainable AI (XAI) methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. FEATURES: Provides the necessary background for newcomers to the field (both academics and interested practitioners) Presents a timely snapshot of explainable and interpretable models in ITS applications Discusses ethical, societal, and legal implications of adopting XAI in the context of ITS Identifies future research directions and open problems
