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Author: Max Cohen Publisher: Springer Nature ISBN: 303129310X Category : Technology & Engineering Languages : en Pages : 209
Book Description
This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. Safety is critical to many applications, such as autonomous driving, air traffic control, and robotics. As these learning-enabled technologies become more prevalent in the control of autonomous systems, it becomes increasingly important to ensure that such systems are safe. To address these challenges, the authors provide a self-contained treatment of learning-based control techniques with rigorous guarantees of stability and safety. This book contains recent results on provably correct control techniques from specifications that go beyond safety and stability, such as temporal logic formulas. The authors bring together control theory, optimization, machine learning, and formal methods and present worked-out examples and extensive simulation examples to complement the mathematical style of presentation. Prerequisites are minimal, and the underlying ideas are accessible to readers with only a brief background in control-theoretic ideas, such as Lyapunov stability theory.
Author: Max Cohen Publisher: Springer Nature ISBN: 303129310X Category : Technology & Engineering Languages : en Pages : 209
Book Description
This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. Safety is critical to many applications, such as autonomous driving, air traffic control, and robotics. As these learning-enabled technologies become more prevalent in the control of autonomous systems, it becomes increasingly important to ensure that such systems are safe. To address these challenges, the authors provide a self-contained treatment of learning-based control techniques with rigorous guarantees of stability and safety. This book contains recent results on provably correct control techniques from specifications that go beyond safety and stability, such as temporal logic formulas. The authors bring together control theory, optimization, machine learning, and formal methods and present worked-out examples and extensive simulation examples to complement the mathematical style of presentation. Prerequisites are minimal, and the underlying ideas are accessible to readers with only a brief background in control-theoretic ideas, such as Lyapunov stability theory.
Author: Zhong-Ping Jiang Publisher: Now Publishers ISBN: 9781680837520 Category : Technology & Engineering Languages : en Pages : 122
Book Description
The recent success of Reinforcement Learning and related methods can be attributed to several key factors. First, it is driven by reward signals obtained through the interaction with the environment. Second, it is closely related to the human learning behavior. Third, it has a solid mathematical foundation. Nonetheless, conventional Reinforcement Learning theory exhibits some shortcomings particularly in a continuous environment or in considering the stability and robustness of the controlled process. In this monograph, the authors build on Reinforcement Learning to present a learning-based approach for controlling dynamical systems from real-time data and review some major developments in this relatively young field. In doing so the authors develop a framework for learning-based control theory that shows how to learn directly suboptimal controllers from input-output data. There are three main challenges on the development of learning-based control. First, there is a need to generalize existing recursive methods. Second, as a fundamental difference between learning-based control and Reinforcement Learning, stability and robustness are important issues that must be addressed for the safety-critical engineering systems such as self-driving cars. Third, data efficiency of Reinforcement Learning algorithms need be addressed for safety-critical engineering systems. This monograph provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.
Author: Wei Xiao Publisher: Springer Nature ISBN: 3031275764 Category : Technology & Engineering Languages : en Pages : 228
Book Description
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 can be easily implemented in real-time systems that require high-frequency reactive control. In addition, the CBF approach can easily deal with nonlinear models and complex constraints used in a wide spectrum of applications, including autonomous driving, robotics, and traffic control. With the proliferation of autonomous systems, such as self-driving cars, mobile robots, and unmanned air vehicles, safety plays a crucial role in ensuring their widespread adoption. This book considers the integration of safety guarantees into the operation of such systems including typical safety requirements that involve collision avoidance, technological system limitations, and bounds on real-time executions. Adaptive approaches for safety are also proposed for time-varying execution bounds and noisy dynamics.
Author: Jesus Hamilton Ortiz Publisher: BoD – Books on Demand ISBN: 1839687398 Category : Technology & Engineering Languages : en Pages : 184
Book Description
Collaborative and Humanoid Robots guides readers through the fundamentals and state-of-the-art concepts and future expectations of robotics. It showcases interesting research topics on robots and cobots by researchers, industry practitioners, and academics. Divided into two sections on “Collaborative Robots” and “Humanoid Robots,” this book includes surveys of recent publications that investigative the interaction between humanoid robots and humans; safe adaptive trajectory tracking control of robots; 3D printed, self-learning robots; robot trajectory, guidance, and control; social robots; Tiny Blind assistive humanoid robots; and more.
Author: Massih-Reza Amini Publisher: Springer Nature ISBN: 3031264126 Category : Computers Languages : en Pages : 680
Book Description
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Author: Gopinath Karmakar Publisher: Springer Nature ISBN: 3031279018 Category : Computers Languages : en Pages : 373
Book Description
This book provides professionals and students with practical guidance for the development of safety-critical computer-based systems. It covers important aspects ranging from complying with standards and guidelines to the necessary software development process and tools, and also techniques pertaining to model-based application development platforms as well as qualified programmable controllers. After a general introduction to the book’s topic in chapter 1, chapter 2 discusses dependability aspects of safety systems and how architectural design at the system level helps deal with failures and yet achieves the targeted dependability attributes. Chapter 3 presents the software development process which includes verification and validation at every stage, essential to the development of software for systems performing safety functions. It also explains how the process helps in developing a safety case that can be independently verified and validated. The subsequent chapter 4 presents some important standards and guidelines, which apply to different industries and in different countries. Chapter 5 then discusses the steps towards complying with the standards at every phase of development. It offers a guided tour traversing the path of software qualification by exploring the necessary steps towards achieving the goal with the help of case studies. Chapter 6 highlights the application of formal methods for the development of safety systems software and introduces some available notations and tools which assist the process. Finally, chapter 7 presents a detailed discussion on the importance and the advantages of qualified platforms for safety systems application development, including programmable controller (PLC) and formal model-based development platforms. Each chapter includes case studies illustrating the subject matter. The book is aimed at both practitioners and students interested in the art and science of developing computer-based systems for safety-critical applications. Both audiences will get insights into the tools and techniques along with the latest developments in the design, analysis and qualification, which are constrained by the regulatory and compliance requirements mandated by the applicable guides and standards. It also addresses the needs of professionals and young graduates who specialize in the development of necessary tools and qualified platforms.
Author: Felix Redmill Publisher: Springer Science & Business Media ISBN: 1447120825 Category : Computers Languages : en Pages : 267
Book Description
The programme for the Second Safety-critical Systems Symposium was planned to examine the various aspects of technology currently employed in the design of safety-critical systems, as well as to emphasise the importance of safety and risk management in their design and operation. assessment There is an even balance of contributions from academia and industry. Thus, industry is given the opportunity to express its views of the safety-critical domain and at the same time offered a glimpse of the technologies which are currently under development and which, if successful, will be available in the medium-term future. In the field of technology, a subject whose importance is increasingly being recognised is human factors, and there are papers on this from the University of Hertfordshire and Rolls-Royce. Increasingly, PLCs are being employed in safety-critical applications, and this domain is represented by contributions from Nuclear Electric and August Computers. Then there are papers on maintainability, Ada, reverse engineering, social issues, formal methods, and medical systems, all in the context of safety. And, of course, it is not possible to keep the 'new' technologies out of the safety-critical domain: there are papers on neural networks from the University of Exeter and knowledge-based systems from ERA Technology.
Author: Mac Schwager Publisher: ISBN: Category : Languages : en Pages : 101
Book Description
To be implementable in safety critical applications, adaptive controllers must be shown to behave strictly according to predetermined specifications. This thesis presents two tools for verifying specifications relevant to practical direct-adaptive control systems. The first tool is derived from an asymptotic analysis of the error dynamics of a direct adaptive controller and uncertain linear plant. The analysis yields a so called Reduced Linear Asymptotic System, which can be used for designing adaptive systems to meet transient specifications. The tool is demonstrated in two design examples from flight mechanics, and verified in numerical simulation. The second tool developed is an algorithm for direct-adaptive control of plants with magnitude saturation constraints on multiple inputs. The algorithm is a non-trivial extension of an existing technique for single input systems with saturation. Boundeness of all signals is proved for initial conditions in a compact region. In addition, the notion of a class of multi-dimensional saturation functions is introduced. The saturation compensation technique is demonstrated in numerical simulation. Finally, these tools are applied to design a direct-adaptive controller for a realistic multi-input aircraft model to accomplish control reconfiguration in the case of unforeseen failure, damage, or disturbances. A novel control design for incorporating control allocation and reconfiguration is introduced. The adaptive system is shown in numerical simulation to have favorable transient qualities and to give a stable response with input saturation constraints.
Author: Yingmin Jia Publisher: Springer Nature ISBN: 9811663289 Category : Technology & Engineering Languages : en Pages : 909
Book Description
This book presents the proceedings of the 17th Chinese Intelligent Systems Conference, held in Fuzhou, China, on Oct 16-17, 2021. It focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth study on a number of major topics such as 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 Flight Vehicles and so on. The book is particularly suited for readers who are interested in learning intelligent system and control and artificial intelligence. The book can benefit researchers, engineers, and graduate students.
Author: Max Cohen
Author: Max Cohen
Author: Zhong-Ping Jiang
Author: Naira Hovakimyan
Author: Wei Xiao
Author: Jesus Hamilton Ortiz
Author: Massih-Reza Amini
Author: Gopinath Karmakar
Author: Felix Redmill
Author: Mac Schwager
Author: Yingmin Jia